Workshop Schedule | |||||
---|---|---|---|---|---|
April 11, 2022 (Monday) | |||||
Timings | Hall 1 | Hall 2 | Hall 3 | Hall 4 | Hall 5 |
9.00-13.00 | IWBT-2022 International Workshop on Blockchain Technologies (IWBT2022) Organizers: Sanjay Chaudhary (Ahmedabad University, India), Krishnasuri Narayanam (IBM Research, India) |
MAQTDS-2022 Managing Air Quality Through Data Science (MAQTDS 2022) Organizers: Girish Agrawal (O.P. Jindal Global University, India), Jai Ganesh (Mphasis Ltd., India) |
PMBD-2022 1st Workshop on Pattern mining and Machine learning in Big complex Databases (PMBD 2022) Organizers: Philippe Fournier-Viger (Shenzhen University, China), Mourad Nouioua (Harbin Institute of Technology Shenzhen, China), Hamido Fujita (Iwate Prefectural University, Japan), Lin Zhang (Tencent.com), Vincent S. Tseng (National Chiao Tung University, Taiwan) |
BDMS-2022 The 8th International Workshop on Big Data Management and Service (BDMS 2022) Organizers: Xiaoling Wang (East China Normal University, China), Kai Zheng (University of Electronic Science and Technology of China), An Liu (Soochow University, China) |
BDQM-2022 The 7th International Workshop on Big Data Quality Management (BDQM 2022) Organizers: Xiaoou Ding (Harbin Institute of Technology, China), Xueli Liu (Tianjin University, China) |
13.00-14.00 | Lunch break | ||||
14.00-18.00 | IWBT2022 (Afternoon session) | MAQTDS 2022 (Afternoon session) | GDMA-2022 The 6th International Workshop on Graph Data Management and Analysis (GDMA 2022) Organizers: Lei Zou (Peking University, China) |
Program Details
1. Keynote Speakers

Prof. Gautam Das
Director of Center for Artificial Intelligence and Big Data (CARIDA) and Database Exploration Laboratory (DBXLAB),
University of Texas at Arlington
Title:
Fairness in Database Querying.
April 12, 2022 (Tuesday), 09.00-10.00, Hall 1
Abstract:
We are being constantly judged by automated decision systems that have been criticized for being sometimes discriminatory and unfair. In this talk, we focus on fairness issues that arise when users perform ad-hoc exploration of databases using commonly available querying mechanisms such as selection/range queries, ranking queries, top-k queries, etc. For example, a user may use such queries to retrieve suitable employment opportunities in a jobs database, dating partners in a matching website, or apartments to rent in a real estate database. We will discuss how such querying mechanisms can give sometimes give results that are discriminatory, and discuss approaches to detect, mitigate and prevent such scenarios from occurring. Our work represents some of the initial steps towards the broader goal of integrating fairness conditions into database query processing and data management.
Bio:
Dr. Das is the Associate Dean for Research, College of Engineering, a Distinguished University Chair Professor of Computer Science and Engineering, Director of the Center for Artificial Intelligence and Big Data (CARIDA), and Director of the Database Exploration Laboratory (DBXLAB) at UT-Arlington. Prior to joining UTA in 2004, he has held positions at Microsoft Research, Compaq Corporation and the University of Memphis. He graduated with a B.Tech in computer science from IIT Kanpur, India in 1983, and with a Ph.D in computer science from the University of Wisconsin, Madison in 1990. He is a Fellow of the IEEE and a member of the ACM.
Dr. Das has published over 200 papers, many of which have appeared in premier data mining, database and algorithms conferences and journals. His work has received several awards, including the Communications of the ACM Research Highlights in 2021, ACM SIGMOD Research Highlights in 2019, IEEE ICDE 10-Year Influential Paper Award in 2012, ACM SIGKDD Doctoral Dissertation Award (honorable mention) in 2014 for his former student, and numerous other awards. He has presented keynotes and invited lectures, tutorials and courses at various universities, research labs, and conferences. He has been on the Editorial Board of the journals ACM Transactions on Database Systems and IEEE Transactions on Knowledge and Data Engineering. He has served in the organization roles of several major conferences, including as General Chair of ACM SIGMOD/PODS 2018.

Tirthankar Lahiri
Senior Vice President,
Data and In-Memory Technologies,
Oracle Corporation.
Title:
Oracle Database In-Memory: The Enterprise, at Warp Speed !
April 13, 2022 (Wednesday), 09.00-10.00, Hall 1
Abstract:
In-memory computing is more than simply about speed. It enables a fundamental transformation in business processes. Just as air travel enabled more than just the ability to travel faster: It enabled a completely new global economy, reshaped politics, and transformed society. Oracle's Database In-Memory feature similarly enables not just faster analytics, but a fundamental rethinking and drastic simplification of the traditional analytic platform. Combined with Oracle's many converged database capabilities that bring together many data models and many workloads, and with Oracle's Autonomous Database platform that makes self-driving machine-learning powered databases a reality, Oracle Database In-Memory allows for the development of a new category of enterprise architectures, with significant reduction in cost and complexity, while providing unmatched performance for both transactional and analytic workloads.
Bio:
Tirthankar Lahiri is Senior Vice President of the Data and In-Memory Technologies area within Oracle Database. This includes the Oracle Database Engine (Transactions, Data formats, Indexes, Advanced Compression, Database In-Memory, the Database Filesystem, etc.), the Oracle TimesTen In-Memory Database, and Oracle NoSQLDB. Tirthankar has 26 years of experience in the database industry and has worked on a number of areas such as Performance, Scalability, Manageability and In-Memory architectures. He has 45 issued and several pending patents and a number of academic publications. He has a B.Tech in Computer Science from the Indian Institute of Technology (Kharagpur) and an MS in Electrical Engineering from Stanford University. He was in the PhD program at Stanford and his research included NUMA Operating Systems (the Hive project) and Semistrucured Data (the Ozone project) before his PhD was superceded by his industrial career.

Ioana Manolescu
Inria and Institut Polytechnique de Paris.
Title:
Teasing journalistic findings out of heterogeneous sources: a data/AI journey.
April 13, 2022 (Wednesday), 13.30-14.30, Hall 1
Abstract:
Freedom of the press is under thread worldwide, and the quality of information that people have access to is dangerously degraded, under the joint threat of non-democratic governments and fake information propagation. The press as an industry needs powerful data management tools to help them interpret the complex reality surrounding us.
Since 2018, I have been cooperating with journalists from Le Monde, France's leading newspaper, in devising tools for analyzing large and heterogeneuos data sources that they are interested in. This research has been embodied in ConnectionLens, a graph ETL tool capable of ingesting heterogeneous data sources into a graph, enriched (with the help of ML methods) with entities extracted from data of any type. On such integrated graphs, we devised novel algorithms for keyword search, and combine them in more recent research with structured querying. The talk describes the architecture and main algorithmic challenges in building and exploiting ConnectionLens graphs, illustrated in particular on an application where we study conflicts of interest in the biomedical domain. This is joint work with A. Anadiotis, O. Balalau, H. Galhardas and many others. ConnectionLens Web site (papers+code): https://team.inria.fr/cedar/connectionlens/
This research has been funded by Agence Nationale de la Recherche AI Chair SourcesSay (https://sourcessay.inria.fr)
Bio:
Ioana Manolescu is a senior researcher at Inria Saclay and a part-time professor at Ecole Polytechnique, France. She is the lead of the CEDAR INRIA team focusing on rich data analytics at cloud scale. She is also the scientific director of LabIA, a program ran by the French government whereas AI problems raised by branches of the local and national French public administration are tackled by French research teams. She is a member of the PVLDB Endowment Board of Trustees, and has been Associate Editor for PVLDB, president of the ACM SIGMOD PhD Award Committee, chair of the IEEE ICDE conference, and a program chair of EDBT, SSDBM, ICWE among others. She has co-authored more than 150 articles in international journals and conferences and co-authored books on "Web Data Management" and on "Cloud-based RDF Data Management". Her main research interests algebraic and storage optimizations for semistructured data, in particular Semantic Web graphs, novel data models and languages for complex data management, data models and algorithms for fact-checking and data journalism, a topic where she is collaborating with journalists from Le Monde. She is also a recipient of the ANR AI Chair titled "SourcesSay: Intelligent Analysis and Interconnexion of Heterogeneous Data in Digital Arenas" (2020-2024).

Prof. Sunita Sarawagi
Institute Chair Professor, Computer Science and Engineering, IIT Bombay.
Title:
Modern AI for Age-old problems of Database Systems.
April 14, 2022 (Thursday), 09.00-10.00, Hall 1
Abstract:
Modern deep learning methods are pushing the frontiers of many challenging problems in database systems. We will discuss state-of-the-art machine learning models that are providing record breaking accuracies on age-old tasks such as entity resolution, missing value imputation and natural language querying. We are also witnessing brand new capabilities that were not possible a few years back. We can perform entity resolution across heterogeneous, multilingual datasets via actively learned nearest neighbor indices, thereby eliminating the need for hand-designing blocking predicates. On multi-dimensional analytical datasets, we can now obtain joint distributions over thousands of interacting time series. Advances in pre-trained language models have significantly increased the capability of handling natural variations in parsing text input to SQL. In this talk we will go over the latest ML research that is enabling these capabilities, and present directions for future research.
Bio:
Sunita Sarawagi researches in the fields of databases and machine learning. She is institute chair professor at IIT Bombay. She got her PhD in databases from the University of California at Berkeley and a bachelors degree from IIT Kharagpur. She has also worked at Google Research (2014-2016), CMU (2004), and IBM Almaden Research Center (1996-1999). She was awarded the Infosys Prize in 2019 for Engineering and Computer Science, and the distinguished Alumnus award from IIT Kharagpur. She has several publications including best paper awards at ACM SIGMOD, VLDB, ICDM, NIPS, and ICML conferences. She has served on the board of directors of the ACM SIGKDD and VLDB foundation. She was program chair for the ACM SIGKDD 2008 conference, research track co-chair for the VLDB 2011 conference and has served as program committee member for SIGMOD, VLDB, SIGKDD, ICDE, and ICML conferences, and on the editorial boards of the ACM TODS and ACM TKDD journals.

Prof. Guoliang Li
Tsinghua University, Beijing, China.
Title:
openGauss: An Autonomous Database System.
April 14, 2022 (Thursday), 13.30-14.30, Hall 1
Abstract:
In this talk, I will present how to build an autonomous database system. I discuss how to integrate effective learning-based models into database systems to build learned optimizers (including learned query rewrite, learned cost/cardinality estimation, learned join order selection and physical operator selection) and learned database advisors (including self-monitoring, self-diagnosis, self-configuration, and self- optimization). I also propose an effective validation model to validate the effectiveness of learned models. I discuss effective training data management and model management platforms to easily deploy learned models. Finally I will introduce our autonomous database system openGauss.
Bio:
Guoliang Li is a full professor and the deputy head of Department of Computer Science, Tsinghua University, Beijing, China. His research interests include large-scale data integration and cleaning, human-in-the-loop data management, machine learning for database, and database for machine learning. He is a general co-chair of SIGMOD 2021, demo co-chair of VLDB 2021, industry co-chair of ICDE 2022, and PC co-chair of DASFAA 2019. He is also an associate editor of VLDB journal and IEEE TKDE. He is a steering committee member of IEEE TCDE and DASFAA. He received best paper awards (candidates) of VLDB 2020, ICDE 2018, KDD 2018, CIKM 2017 and DASFAA 2014. He received Early Research Contribution Award of VLDB and Early Career Award of IEEE TCDE.
2. Panel Session
Title:
Futuristic Data Interfaces
Hall 1, April 12, 2022 (Tuesday), 17:00-18:30 India Time
Overview:
Database systems have been around for more than four decades and have been widely used in academia and industry across the globe. In this panel we discuss the following two questions from various perspectives with four different internationally renowned database experts.
- What are the challenges of current database interfaces?
- What solutions do you propose to solve these challenges?
Moderator:

Kurt Stockinger
Zurich University of Applied Sciences,
Switzerland.
Panelists:

Georgia Koutrika
Athena Research,
Greece.

Jaydeep Sen
IBM Research,
India.

Immanuel Trummer
Cornell University,
USA.

Lei Zou
Peking University,
China.
Moderator: Kurt Stockinger (Zurich University of Applied Sciences, Switzerland)
Bio: Prof. Dr. Kurt Stockinger is Professor of Computer Science, Director of Studies in Data Science at Zurich University of Applied Sciences (ZHAW) and Co-Head of the ZHAW Datalab. His research focuses on Data Science with emphasis on Big Data, Natural Language Query Processing, Query Optimization and Quantum Computing. Essentially, his research interests are at the intersection of databases, natural language processing and machine learning. He is also on the Advisory Board of Callista Group AG and the International AIQT Foundation. Previously Kurt Stockinger worked at Credit Suisse in Zurich, Switzerland, at Lawrence Berkeley National Laboratory in Berkeley, California, at California Institute of Technology, California as well as at CERN in Geneva, Switzerland. He holds a Ph.D. in computer science from CERN / University of Vienna.
(i) Georgia Koutrika (Athena Research, Greece)
Title: Intelligent Data Assistants
Abstract: Data is considered the 21st century’s most valuable commodity. Analysts exploring data sets for insight, scientists looking for patterns, and consumers looking for information are just a few examples of user groups that need to access and dig into data. Despite technological advances in the data exploration and data management domains, existing systems are falling behind in bridging the chasm between data and users, making data accessible and useful only to the few. A futuristic data interface would enable interaction with data using natural language, would understand the data as well as the user intent, would guide the user, and make suggestions, and altogether help the user leverage data for all sorts of purposes (from finding answers to questions to revealing patterns and finding solutions to problems) in a more natural way. These systems, which we call intelligent data assistants, require the synergy of several technologies and innovation in all these fronts, including natural language interfaces, data exploration, conversational AI, and data management.
Bio: Georgia Koutrika is a Research Director at Athena Research Center in Greece. She has more than 15 years of experience in multiple roles at HP Labs, IBM Almaden, and Stanford. Her work emerges at the intersection of data management, natural language processing and deep learning and focuses on intelligent and interactive data exploration, conversational data systems, and user-driven data management. Her work has been incorporated in commercial products, described in 14 granted patents and 26 patent applications in the US and worldwide, and published in more than 100 papers in top-tier conferences and journals. Georgia is an ACM Senior Member and IEEE Senior Member. She is a member of the VLDB Endowment Board of Trustees, member of the PVLDB Advisory Board, member of the ACM-RAISE Working Group, co-Editor-in-chief for VLDB Journal, PC co-chair for VLDB 2023, co-EiC of Proceedings of VLDB (PVLDB). She has been associate editor in top-tier conferences (such as ACM SIGMOD, VLDB) and journals (VLDB Journal, IEEE TKDE), and she has been in the organizing committee of several conferences including SIGMOD, ICDE, EDBT, among others. She has received a PhD and a diploma in Computer Science from the Department of Informatics and Telecommunications, University of Athens, Greece.
(ii) Jaydeep Sen (IBM Research, India)
Title: Evolution of NLIDB systems and their application in Industry setups
Abstract:: In this modern era of technology, multitude of business applications are rapidly moving towards data driven insights for intelligent decision making, analytics and more. As we continue to see heaps of digital exhaust being generated, access to data is still limited to technical users who can query the datastores with specific query languages. Natural Language Interface to Databases (NLIDB) systems have gained a lot of focus recently owing to its fascinating aim of democratizing data access to non-technical business users. The research space for NL interfaces for data has evolved a lot since its inception, starting from simple keyword based queries, all the way to machine learning based systems, also dubbed as text-to-sql challenge. While the appeal of NLIDB system is common across different persona and use-cases, deploying a NLIDB system for an industry application has its own set of challenges which are often closely coupled with the exact domain and use-case. With no "one size fits all" solution in place, it is the right time for the community to review how the different methodologies adopted for NLIDB systems correlate with their applicability across different use-cases seen in academia and industry.
Bio: Jaydeep Sen is a Research Staff Member in IBM Research AI, India Lab . His research interests include applications for natural language understanding, semantic reasoning, designing intelligent algorithms for “learning from small data” applications. His work at IBM has powered some of IBM's most prominent QA and NL application portfolio. He has publications at conferences like VLDB, SIGMOD, IJCAI, IEEE SCC, EMNLP, COLING etc. and has served as Program Committee members for AAAI, SIGMOD, ICDE etc. He has more than 20 patents (granted/filed) in USPTO as of Dec-2021.
(iii) Immanuel Trummer (Cornell University, USA)
Title: Voice Interfaces for Data Access
Abstract:The communication between user and user is shifting more and more towards voice interfaces. This trend is evidenced by devices and services such as Google Home, Amazon Alexa, or Apple’s Siri. For many users, speech is the most natural form of interaction. It enables computer use from a distance, even in scenarios where hands or the visual attention are bound (e.g., while driving). All those advantages motivate the question of how to leverage voice interfaces for convenient data access. Accessing data via voice query interfaces is challenging. First, noisy speech recognition adds uncertainty on top of the inherent difficulties of natural language understanding. Second, transferring query results to users via voice output is difficult. Verbose speech output risks overwhelming the listener. Hence, output needs to summarize and to focus on the most important trends in the data. Recent research tackles some of those challenges. Still, many research questions remain open and must be answered to make the vision of natural data access via voice query interfaces a reality.
Bio: Immanuel Trummer is assistant professor at Cornell University, working towards making data analysis more efficient and more user-friendly. His papers were selected for “Best of VLDB”, “Best of SIGMOD”, for the ACM SIGMOD Research Highlight Award, and for publication in CACM as CACM Research Highlight. His current research is funded by the NSF and by multiple Google Faculty Research Awards.
(iv) Lei Zou (Peking University, China)
Title: Natural Language Question Answering over Knowledge Graph
Abstract: AS more and more structured data become available on the web, the question of how end users can access this body of knowledge becomes of crucial importance. As a de facto standard of a knowledge base, RDF (Resource Description Framework) repository is a collection of triples, denoted as
Generally, there are two categories of existing methods on natural language question answering (Q/A) over RDF database---one is IR (Information Retrieval)-based and the other one is called semantic parsing method. In this panel, I will talk about our solution gAnswer, which is based on graph matching-based technique, to design an effective natural language interface to access KG database.
Bio: Lei Zou is a professor at Peking University, China, and his recent research interests include graph databases, knowledge graph, particularly in graph-based RDF data management, natural language question answering over knowledge graph, hardware assisted graph database systems. Lei Zou’s research is supported by multiple NSFC projects. Prof. Zou also obtained Newton Advanced Fellowships of UK Royal Society. Lei Zou has publications at conferences like VLDB, SIGMOD, ICDE etc, and has served as Program Committee members for SIGMOD, VLDB and ICDE. He served PC Area Chair of ICDE 2021 and PC Chair of WISE 2022. Now, he is an Associate Editor of IEEE Transactions on Knowledge and Data Engineering (TKDE).
3. Tutorial talks
Date and Time (Hall) | Tutorial talks |
Tutorial 1 (April 12 (Tuesday), 2022, 14:45 to 16:30, Hall 5) |
Title:Make Wise Decisions for Your DBMSs: Workload Forecasting and Performance Prediction Before ExecutionSpeakers:
Brief outline of the tutorial:Speakers Bio |
Tutorial 2 (April 12 (Tuesday), 2022, 10:15 to 12.30, Hall 5) |
Title:Reachability on Large-scale Graphs: Models, Techniques, and TrendsSpeakers:
Brief outline of the tutorial:Speakers Bio |
Tutorial 3 (April 13 (Wednesday), 2022, 10:15 to 12:30, Hall 5) |
Title:A tutorial on biomedical image segmentation using deep learningSpeakers:
Brief outline of the tutorial:Speakers Bio |
Tutorial 4 (April 13 (Wednesday), 2022, 14:30 to 16:15, Hall 5) |
Title:AI Meets NoSQL Database: Methods, Opportunities and ChallengesSpeakers:
Brief outline of the tutorial:(1) Background and Motivation (10’): We introduce the background of AI for database and motivate the need for applying AI techniques on NoSQL database with several scenarios. (2) Cost Estimation for Graph and Document Databases (20’): We discuss how AI techniques estimate query costs for graph and document databases. (3) Physical Design for Key-Value and Graph Databases (20’): We introduce physical design methods for key-value and graph databases based on AI techniques. (4) Index Recommendation for Key-Value and Document Databases (15’): We discuss existing AI-based index recommendation approaches for key-value and document databases. (5) Opportunities and Challenges (20’): We present the research opportunities and challenges for NoSQL database management based on AI techniques. (6) Summary (5’): We summarize this tutorial and give our critical thoughts to AI for NoSQL database. Speakers Bio |
Tutorial 5 (April 14 (Thursday), 2022, 10:15 to 12:30, Hall 5) |
Title:Time Series Anomaly Detection Toolkit for AI Applications [Slides]Speakers:
Brief outline of the tutorial:Speakers Bio |
4. Workshops (April 11, 2022, Monday, 09.00- 18.00)
Workshop Name | Program |
International Workshop on Blockchain Technologies (IWBT2022) | https://sites.google.com/ahduni.edu.in/iwbt2022/home 9:00 – 9:15 (IST) "Welcome and Introduction" by Dr. Sanjay Chaudhary, Workshop co-chair, Dean and Professor, Ahmedabad University 9:15 - 10:15 (IST) Keynote Talk: "From Impossible Triangles to innovations through Blockchains" by Professor C. Pandu Rangan, Sathish Dhawan Chair professor, Computer science and Automation, IISc, Bangalore, India 10:15 to 11:00 (IST) Invited Talk: "SnarkWars: The promise of Zero Knowledge Proofs for Scaling Blockchains" by Dr. Nitin Singh, Senior Research Scientist, IBM Research India 11:00 - 11:15 (IST) Tea / Coffee Break 11:15 - 12:00 (IST) Invited Talk: "Proofs of Storage and Applications" by Dr. Sushmita Ruj, Senior Lecturer, School of Computer Science and Engineering, UNSW, Sydney 12:00 - 12:30 (IST) Research Paper Presentation "Securing Cookies/Sessions through Non-Fungible Tokens" by Dr. Kaushal Shah, Uday Khokhariya, Nidhay Pancholi, Shambhavi Kumar and Keyur Parmar, Pandit Deendayal Energy University (PDEU), Gandhinagar, India 12:30 - 14:00 (IST) Lunch Break 14:00 - 14:45 (IST) Invited Talk “Next-Generation Blockchains -- Potential and Challenges” by Dr. Sujit Prakash Gujar, Assistant Professor, International Institute of Information Technology, Hyderabad, India 14:45 - 16:15(IST) Research Paper Presentations "Towards a Blockchain Solution for Customs Duty-Related Fraud" by Dr. Christopher G. Harris, Associate Professor, Computer Science, School of Mathematical Sciences, University of Northern Colorado, USA (14:45 - 15:15) "Model-Driven Development of Distributed Ledger Applications" by Piero Fraternali, Dr. Sergio Luis Herrera Gonzalez, Matteo Frigerio and Mattia Righetti, Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Piazza Leonardo da Vinci 32, Milan, Italy (15:15 - 15:45) "Collaborative Blockchain based Distributed Denial of Service Attack Mitigation approach with IP Reputation System" by Darshi Patel and Dr. Dhiren Patel, Gujarat Vidyapith, India (15:45 - 16:15) 16:15 - 16:30(IST) Tea / Coffee Break 16:30 - 17:30(IST) Panel Discussion on "Trends and Challenges in the adoption of blockchain for real-world problems" by Dr. Raghavendra Deshmukh, Engineering Leader, Google Dr. Sandip Chakraborty, Associate Professor, Indian Institute of Technology, Kharagpur, West Bengal, India Dr. Anu Singh, Blockchain Supply Chain Transformation Leader, IBM 17:30 - 17:45(IST) Concluding Remarks by Dr. Krishnasuri Narayanam, Workshop co-chair, Senior Research Software Engineer, IBM Research, India |
Managing Air Quality Through Data Science | https://cs.ashoka.edu.in/maqtds/ 9:30 – 9:45 AM(IST) Welcome and Introduction to Workshop 9:45 – 10:00 AM(IST) Opening address by "Prof. Gautam Menon, Director, Centre for Climate Change and Sustainability (3CS) at Ashoka University" 10:00 – 11:00 AM(IST) Keynote 1: Big Data Resources to Support Research Opportunities on Air Pollution Analysis in India by "Dr. Sarath Guttikunda, Adjunct Faculty, TRIP-C, IIT Delhi, and Founder/ Director, Urban Emissions" 11:00 – 11:15 AM(IST) Break 11:15 – 11:45 AM(IST) Presentation 1: Leveraging geospatial technology for air quality monitoring by "Tejasvini Puri, BlueSky Analytics" 11:45 AM – 12:15 PM(IST) Presentation 2: Visualizing Spatio-Temporal Variation of Ambient air pollution in selected small cities in India by "Prof. Girish Agrawal & Hifzur Rahman, OP Jindal Global University" 12:15 – 1:15 PM(IST) Lunch Break 1:15 – 1:45 PM(IST) Presentation 3: Air Quality Data Collection in Hyderabad using Low Cost Sensors: Initial Experiences by "Srinivas Annappalli & Chandra Shekar N, IIIT Hyderabad" 1:45 – 2:45 PM(IST) Keynote 2: Making air pollution legible! Data and governance in Indian cities by "Dr. Anant Maringanti, Director, Hyderabad Urban Lab" 2:45 – 3:15 PM(IST) Presentation 4: AIR-Tree: Air-quality Indices based R-Tree for Air-Quality Data Management by "Prof. Anirban Mondal & Mr. Raghav Mittal, Ashoka University" 3:15 – 4:00 PM(IST) Panel Discussion moderated by Prof. Anirban Mondal: Collaboration across a range of STEM and social sciences disciplines towards air quality improvement Dr. Jai Ganesh (Mphasis) Mr. Vikas Sahni (Ashoka University) Dr. Anant Maringanti (Hyderabad Urban Lab) Prof. Girish Agrawal (OP Jindal Global University) Prof. P. Krishna Reddy (IIIT Hyderabad) 4:00 – 4:15 PM(IST) Closing Remarks |
1st Workshop on Pattern mining and Machine learning in Big complex Databases (PMBD 2022) | https://philippe-fournier-viger.com/PMDB_2021/program.html 8:30 AM(IST) Opening of the workshop 8:45 AM(IST) Keynote Talk: Approximate Computing for Big Data Analysis by Distinguished Prof. Joshua Zhexue Huang 9:45 AM(IST) Paper #2 An Algorithm for Mining Fixed-Length High Utility Itemsets by "Le Wang" 10:05 AM(IST) Paper #3 A Novel Method to Create Synthetic Samples with Autoencoder Multi-layer Extreme Learning Machine by "Qihang Huang, Yulin He, Shengsheng Xu and Joshua Zhexue Huang" 10:25 AM(IST) Paper #4 Pattern Mining: Current Challenges and Opportunities by "Philippe Fournier-Viger, Wensheng Gan, Youxi Wu, Mourad Nouioua, Wei Song, Tin Truong and Hai Duong Van" 10:45 AM(IST) Paper #7 Why not to Trust Big Data: Identifying Existence of Simpson’s Paradox by "Rahul Sharma, Minakshi Kaushik, Sijo Arakkal Peious, Mahtab Shahin, Ankit Vidhyarthi and Dirk Draheim" 11:05 AM(IST) Paper #8 Localized Metric Learning for Large Multi-Class Extremely Imbalanced Face Database by "Seba Susan and Ashu Kaushik" 11:25 AM(IST) Paper #9 Top-k dominating queries on incremental datasets by "Jimmy Ming-Tai Wu, Ke Wang and Jerry Chun-Wei Lin" 11:45 AM(IST) Closing of the workshop |
The 8th International Workshop on Big Data Management and Service (BDMS 2022) |
https://zheng-kai.com/cfp 9.00-12.30 AM(IST) Morning session Session Chair: Kevin Zheng, An Liu, Xiaoling Wang BDMS001: H-V:An Improved Coding Layout based on Erasure Coded Storage System (9:00-9:20) BDMS002: An Autoencoder-based Model for Pedestrian Trajectory Prediction of Variable-Length (9:20-9:40) BDMS003: A Survey on Spatiotemporal Data Processing Techniques in Smart Urban Rail (9:40-10:00) BDMS004: Fast Vehicle Track Counting in Traffic Video (10:00-10:20) BDMS005: TSummary A Traffic Summarization System using Semantic Words (10:20-10:40) BDMS006: Attention Cooperated Reinforcement Learning for Multi agent Path Planning (10:40-11:00) BDMS007: Big Data-driven Stable Task Allocation in Ride-hailing Services (11:00-11:20) BDMS008: Weighted Mean Field Multi Agent Reinforcement Learning via Reward Attribution Decomposition (11:20- 11:40) Keynotes: Zero-Shot Event Extraction Based on Contrastive Learning (11:40-12:30) by Wendi Ji |
The 7th International Workshop on Big Data Quality Management (BDQM 2022) | https://bdqm2022.github.io/ 9:00-10:10 AM(IST) Invited Talk: Title: Big Data Management and Analytics via Direct Computing on Compression by "Feng Zhang, Renmin University of China". 10:10-11:20 AM(IST) Invited Talk: Title: Data Quality Management: Turn Waste into Wealth by "Shaoxu Song, Tsinghua University, China". 11:20-12:50 AM(IST) Paper presentations Evaluating Presto and SparkSQL with TPC-DS by "Yinhao Hong, Sheng Du, Jianquan Leng (Renmin University of China, Beijing Kingbase Information Technology Co., Ltd, Beijing, China)" Optimizing the Age of Sensed Information in Cyber-Physical Systems by "Yinlong Li,Siyao Cheng,Feng Li, Jie Liu, Hanling Wu (Harbin Institute of Technology, Harbin Institute of Technology(shenzen), Beijing Institute of Astronautical Systems Engineering, China)" Aggregate Query Result Correctness using Pattern Tables by "Nitish Yadav, Ayushi Malhotra, Sakshee Patel, Minal Bhise (Distributed Databases Group, DAIICT, Gandhinagar, India)" Time Series Data Quality Enhancing based on Pattern Alignment by "Jianping Huang, Hao Chen, Hongkai Wang, Jun Feng, Liangying Peng, Zheng Liang, Hongzhi Wang, Tianlan Fan, Tianren Yu (State Grid Zhejiang Electric Power Co., Ltd, State Grid Zhejiang Information and Telecommunication Branch, China, Harbin Institute of Technology)" Research on feature extraction method of data quality intelligent detection by "Weiwei Liu,Shuya Lei, Xiaokun Zheng, Xiao Liang (Artificial Intelligence on Electric Power System State Grid Corporation Joint Laboratory(GEIRI) China)" |
The 6th International Workshop on Graph Data Management and Analysis (GDMA 2022) | https://gdma2022.github.io/ 14:00-14:35 (IST) Keynote by Tieyun Qian (Wuhan University) Title: Diversity and Novelty Oriented Recommendation for Long-tailed Items 14:35-15:10 (IST) Keynote by Peng Peng (Hunan University) Title: Distributed RDF Graph Management 15:20-16:45 (IST) (Oral Paper) Chinese Spelling Error Detection and Correction Based on Knowledge Graph 16:45-17:10 (IST) (Oral Paper) Construction and Application of Event Logic Graph: A Survey 17:10-17:35 (IST) (Oral Paper) Enhancing Low-resource Languages Question Answering with Syntactic Graph 17:35-18:00 (IST) (Oral Paper) Profile Consistency Discrimination |
5. Research Sessions
Research Session Id | Session Name | Paper ID | Paper Title |
(Date, Time, and Hall) | |||
1 |
Research Session #1 (Queries)
(April 12 (Tuesday), 2022, 10.15-12.30, Hall 1) |
20 |
Approximate Continuous Top-K Queries Over Memory Limitation-based Streaming Data
[Abstract] |
Rui Zhu (School of Computer Science, Shenyang Aerospace University, China); Liu Meng (School of Computer Science, Shenyang Aerospace University, China); Bin Wang (College of Computer Science and Engineering, Northeastern University, China); Xiaochun Yang (College of Computer Science and Engineering, Northeastern University, China); Xiufeng Xia (School of Computer Science, Shenyang Aerospace University, China); | |||
22 |
Cross-Model Conjunctive Queries over Relation and Tree-structured Data
[Abstract] |
||
Yuxing Chen (University of Helsinki); Valter Uotila (University of Helsinki); Jiaheng Lu (University of Helsinki); Zhen Hua Liu (Oracle); Souripriya Das (Oracle); | |||
178 |
Leveraging Search History for Improving Person-Job Fit
[Abstract] |
||
Yupeng Hou (Gaoling School of Artificial Intelligence, Renmin University of China, China); Xingyu Pan (School of Information, Renmin University of China, China); Wayne Xin Zhao (Gaoling School of Artificial Intelligence, Renmin University of China, China); Shuqing Bian (School of Information, Renmin University of China, China); Yang Song (BOSS Zhipin, Beijing, China); Tao Zhang (BOSS Zhipin, Beijing, China); Ji-Rong Wen (Gaoling School of Artificial Intelligence, Renmin University of China, China); | |||
503 |
Efficient In-Memory Evaluation of Reachability Graph Pattern Queries on Data Graphs
[Abstract] |
||
Xiaoying Wu (Wuhan University, China); Dimitri Theodoratos (New Jersey Institute of Technology, USA); Dimitrios Skoutas (R.C. Athena, Athens, Greece); Michael Lan (New Jersey Institute of Technology, USA); | |||
523 |
Revisiting Approximate Query Processing and Bootstrap Error Estimation on GPU
[Abstract] |
||
Hang Zhao (Fudan University, Shanghai, China); Hanbing Zhang (Fudan University, Shanghai, China); Yinan Jing (Fudan University, Shanghai, China); Kai Zhang (Fudan University, Shanghai, China); Zhenying He (Fudan University, Shanghai, China); X. Sean Wang (Fudan University, Shanghai, China); | |||
257 |
μ-join: Efficient Join with Versioned Dimension Tables
[Abstract] |
||
Mika Takata (The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo, Japan); Kazuo Goda (The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo, Japan); Masaru Kitsuregawa (The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo, Japan); | |||
532 |
Learning-based Optimization for Online Approximate Query Processing
[Abstract] |
||
Wenyuan Bi (Fudan University, Shanghai, China); Hanbing Zhang (Fudan University, Shanghai, China); Yinan Jing (Fudan University, Shanghai, China); Zhenying He (Fudan University, Shanghai, China); Kai Zhang (Fudan University, Shanghai, China); X. Sean Wang (Fudan University, Shanghai, China); | |||
2 |
Research Session #2 (Text and Image-I),
(April 12 (Tuesday), 2022, 10.15-12.30, Hall 2) |
65 |
Emotion-aware Multimodal Pre-training for Image-grounded Emotional Response Generation
[Abstract] |
Zhiliang Tian (The Hong Kong University of Science and Technology, Hong Kong SAR, China); Zhihua Wen (Science and Technology on Parallel and Distributed Laboratory, National University of Defense Technology, Hunan, China); Zhenghao Wu (The Hong Kong University of Science and Technology, Hong Kong SAR, China); Yiping Song (National University of Defense Technology, Hunan, China); Jintao Tang (National University of Defense Technology, Hunan, China); Dongsheng Li (Science and Technology on Parallel and Distributed Laboratory, National University of Defense Technology, Hunan, China); Nevin L. Zhang (The Hong Kong University of Science and Technology, Hong Kong SAR, China); | |||
416 |
KdTNet: Medical Image Report Generation via Knowledge-driven Transformer
[Abstract] |
||
Yiming Cao (School of Software, Shandong University, China); Lizhen Cui (Joint SDU-NTU Centre for Artificial Intelligence Research (C-FAIR), Shandong University, China); Fuqiang Yu (School of Software, Shandong University, China); Lei Zhang (School of Software, Shandong University, China); Zhen Li (Department of Gastroenterology, Qilu Hospital of Shandong University, China); Ning Liu (School of Software, Shandong University, China); Yonghui Xu (Joint SDU-NTU Centre for Artificial Intelligence Research (C-FAIR), Shandong University, China); | |||
464 |
AdCSE: An Adversarial Method for Contrastive Learning of Sentence Embeddings
[Abstract] |
||
Renhao Li (School of Computer Science, Sichuan University, Chengdu, China); Lei Duan (School of Computer Science, Sichuan University, Chengdu, China); Guicai Xie (School of Computer Science, Sichuan University, Chengdu, China); Shan Xiao (School of Computer Science, Sichuan University, Chengdu, China); Weipeng Jiang (School of Computer Science, Sichuan University, Chengdu, China); | |||
502 |
HRG: A Hybrid Retrieval and Generation model in Multi-turn Dialogue Generation
[Abstract] |
||
Deji Zhao (School of Information Science and Technology, Dalian Maritime University, Dalian, China); Xinyi Liu (School of Information Science and Technology, Dalian Maritime University, Dalian, China); Bo Ning (School of Information Science and Technology, Dalian Maritime University, Dalian, China); Chengfei Liu (Swinburne University of Technology, Australia); | |||
122 |
SimEmotion: A Simple Knowledgeable Prompt Tuning Method for Image Emotion Classification
[Abstract] |
||
Sinuo Deng (Faculty of Information Technology, Beijing University of Technology, Beijing, China); Ge Shi (Faculty of Information Technology, Beijing University of Technology, Beijing, China); Lifang Wu( (Faculty of Information Technology, Beijing University of Technology, Beijing, China); Lehao Xing (Faculty of Information Technology, Beijing University of Technology, Beijing, China); Wenjin Hu (Faculty of Information Technology, Beijing University of Technology, Beijing, China); Heng Zhang (Faculty of Information Technology, Beijing University of Technology, Beijing, China); Ye Xiang (Faculty of Information Technology, Beijing University of Technology, Beijing, China); | |||
196 |
E-commerce Knowledge Extraction via Multi-modal Machine Reading Comprehension
[Abstract] |
||
Chaoyu Bai (School of Cyber Science and Engineering, Southeast University, Nanjing, China); | |||
403 |
Concurrent Transformer for Spatial-Temporal Graph Modeling
[Abstract] |
||
Yi Xie (School of Computer Science, Fudan University, Shanghai, China); Yun Xiong (School of Computer Science, Fudan University, Shanghai, China); Yangyong Zhu (School of Computer Science, Fudan University, Shanghai, China); Philip S. Yu (University of Illinois at Chicago, Chicago, U.S.A); Cheng Jin (Shanghai Meteorological Disaster Prevention Technology Center, Shanghai, China); Qiang Wang (Shanghai Meteorological Disaster Prevention Technology Center, Shanghai, China); Haihong Li (Shanghai Meteorological Disaster Prevention Technology Center, Shanghai, China); | |||
519 |
Modeling Uncertainty in Neural Relation Extraction
[Abstract] |
||
Hang Zhao (School of Computer Science, Fudan University, Shanghai, China); Hanbing Zhang (School of Computer Science, Fudan University, Shanghai, China); Yinan Jing (School of Computer Science, Fudan University, Shanghai, China); Kai Zhang (School of Computer Science, Fudan University, Shanghai, China); Zhenying He (School of Computer Science, Fudan University, Shanghai, China); X. Sean Wang (School of Computer Science, Fudan University, Shanghai, China); | |||
3 |
Research Session #3 (Applications of ML-I),
(April 12 (Tuesday), 2022, 10.15-12.30, Hall 3) |
174 |
Similarity-Aware Collaborative Learning for Patient Outcome Predcition
[Abstract] |
Fuqiang Yu (School of Software, Shandong University, China); Lizhen Cui (Joint SDU-NTU Centre for Artificial Intelligence Research (C-FAIR), Shandong University, China); Yiming Cao (School of Software, Shandong University, China); Ning Liu (School of Software, Shandong University, China); Weiming Huang (School of Software, Shandong University, China); Yonghui Xu (Joint SDU-NTU Centre for Artificial Intelligence Research (C-FAIR), Shandong University, China); | |||
252 |
Heterogeneous Federated Learning via Grouped Sequential-to-Parallel Training
[Abstract] |
||
Shenglai Zeng (Sch of Info & Comm Engin, University of Electronic Science and Technology of China, Chengdu, China); Zonghang Li (Sch of Info & Comm Engin, University of Electronic Science and Technology of China, Chengdu, China); Hongfang Yu (Sch of Info & Comm Engin, University of Electronic Science and Technology of China, Chengdu, China); Yihong He (Sch of Info & Comm Engin, University of Electronic Science and Technology of China, Chengdu, China); Zenglin Xu (Sch of Comp Sci & Tech, Harbin Institute of Technology, Shenzhen, China); Dusit Niyato (Sch of Comp Sci & Engin, Nanyang Technological University, Singapore); Han Yu (Sch of Comp Sci & Engin, Nanyang Technological University, Singapore); | |||
335 |
Peripheral Instance Augmentation for End-to-End Anomaly Detection using Weighted Adversarial Learning
[Abstract] |
||
Weixian Zong (School of Data Science and Engineering, East China Normal University, Shanghai, China); Fang Zhou (School of Data Science and Engineering, East China Normal University, Shanghai, China); Martin Pavlovski (Temple University, Philadelphia, United States); Weining Qian (School of Data Science and Engineering, East China Normal University, Shanghai, China); | |||
342 |
HieNet: Bidirectional Hierarchy Framework for Automating ICD Coding
[Abstract] |
||
Shi Wang (Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, China); Daniel Tang (University of Luxembourg, Interdisciplinary Centre for Security, Reliability and Trust (SNT), TruX, Luxembourg); Luchen Zhang (National Computer Network Emergency Response Technical Team/Coordination Center of China); Huilin Li (Department of Civil Engineering, Technical University of Denmark, 2800 Lyngby, Denmark); Ding Han (Huazhong University of Science and Technology, China); | |||
2 |
Data Source Selection in Federated Learning: A Submodular Optimization Approach
[Abstract] |
||
Ruisheng Zhang (State Key Laboratory of Software Development Environment, Beihang University, China); Yansheng Wang (State Key Laboratory of Software Development Environment, Beihang University, China); Zimu Zhou (Singapore Management University, Singapore, Singapore); Ziyao Ren (State Key Laboratory of Software Development Environment, Beihang University, China); Yongxin Tong (State Key Laboratory of Software Development Environment, Beihang University, China); Ke Xu (State Key Laboratory of Software Development Environment, Beihang University, China); | |||
41 |
CLZT:A Contrastive Learning Based Framework for Zero-Shot Text Classification
[Abstract] |
||
Kun Li (School of Cyber Security, University of Chinese Academy of Sciences, China); Meng Lin (School of Cyber Security, University of Chinese Academy of Sciences, China); Songlin Hu (School of Cyber Security, University of Chinese Academy of Sciences, China); Ruixuan Li (Institute of Information Engineering, Chinese Academy of Sciences, China); | |||
248 |
An Interpretable Time Series Classification Approach Based on Feature Clustering
[Abstract] |
||
Fan Qiao (Fudan University, Shanghai, China); Peng Wang (Fudan University, Shanghai, China); Wei Wang (Fudan University, Shanghai, China); Binjie Wang (Beijing Jiaotong University, Beijing, China); | |||
332 |
Supervised Multi-view Latent Space Learning by Jointly Preserving Similarities across Views and Samples
[Abstract] |
||
Xiaoyang Li (School of Data Science and Engineering, East China Normal University, Shanghai, China); Martin Pavlovski (Temple University, Philadelphia, Pennsylvania, United States); Fang Zhou (School of Data Science and Engineering, East China Normal University, Shanghai, China); Qiwen Dong (School of Data Science and Engineering, East China Normal University, Shanghai, China); Weining Qian (School of Data Science and Engineering, East China Normal University, Shanghai, China); Zoran Obradovic (Temple University, Philadelphia, Pennsylvania, United States); | |||
4 |
Research Session #4 (Graphs-I),
(April 12 (Tuesday), 2022, 14.45-16.30 , Hall 1) |
11 |
Cascade-Enhanced Graph Convolutional Network for Information Diffusion Prediction
[Abstract] |
Ding Wang (School of Cyber Security, University of Chinese Academy of Sciences); Lingwei Wei (School of Cyber Security, University of Chinese Academy of Sciences); Chunyuan Yuan (JD.com, Beijing, China); Yinan Bao (School of Cyber Security, University of Chinese Academy of Sciences); Wei Zhou (School of Cyber Security, University of Chinese Academy of Sciences); Xian Zhu (School of Cyber Security, University of Chinese Academy of Sciences); Songlin hu (School of Cyber Security, University of Chinese Academy of Sciences); | |||
15 |
Diversify Search Results through Graph Attentive Document Interaction
[Abstract] |
||
Xianghong Xu (Shenzhen International Graduate School, Tsinghua University, China); Kai Ouyang (Shenzhen International Graduate School, Tsinghua University, China); Yin Zheng (Department of Search and Application, Weixin Group, Tencent, China); Yanxiong Lu (Department of Search and Application, Weixin Group, Tencent, China); Hai-Tao Zheng (Shenzhen International Graduate School, Tsinghua University, China); Hong-Gee Kim (Seoul National University, South Korea); | |||
365 |
Learning Robust Representation through Graph Adversarial Contrastive Learning
[Abstract] |
||
Jiayan Guo (School of Artificial Intelligence, Peking University, Beijing, China); , Shangyang Li (Peking-Tsinghua Center for Life Sciences, IDG/McGovern Institute for Brain Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China); , Yue Zhao (Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China); Yan Zhang (School of Artificial Intelligence, Peking University, Beijing, China); | |||
197 |
Contrastive Disentangled Graph Convolutional Network for Weakly-supervised Node Classification
[Abstract] |
||
Xiaokai Chu (Institute of Computing Technology, Chinese Academy of Sciences, China); Jiashu Zhao (Wilfrid Laurier University, Canada); Xinxin Fan (Institute of Computing Technology, Chinese Academy of Sciences, China); Di Yao (Institute of Computing Technology, Chinese Academy of Sciences, China); Zhihua Zhu (Institute of Computing Technology, Chinese Academy of Sciences, China); Lixin Zou (Baidu Inc., China); Dawei Yin (Baidu Inc., China); Jingping Bi (Institute of Computing Technology, Chinese Academy of Sciences, China); | |||
353 |
CSGNN: Improving Graph Neural Networks with Contrastive Semi-Supervised Learning
[Abstract] |
||
Yumeng Song (School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China); Yu Gu (School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China); Xiaohua Li (School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China); Chuanwen Li (School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China); Ge Yu (School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China); | |||
5 |
Research Session #5 (Text and Image-II),
(April 12 (Tuesday), 2022, 14.45-16.30 , Hall 2) |
271 |
Tracking the Evolution: Discovering and Visualizing the Evolution of Literature
[Abstract] |
Siyuan Wu (State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science University of Macau, Macau SAR, China); Leong Hou U (State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science University of Macau, Macau SAR, China); | |||
323 |
Incorporating Commonsense Knowledge into Story Ending Generation via Heterogeneous Graph Networks
[Abstract] |
||
Jiaan Wang (School of Computer Science and Technology, Soochow University, Suzhou, China); Beiqi Zou (Department of Computer Science, Princeton University, USA); Zhixu Li (Shanghai Key Laboratory of Data Science, School of Computer Science, Fudan University, Shanghai, China); Jianfeng Qu (School of Computer Science and Technology, Soochow University, Suzhou, China); Pengpeng Zhao (School of Computer Science and Technology, Soochow University, Suzhou, China); An Liu (School of Computer Science and Technology, Soochow University, Suzhou, China); Lei Zhao (School of Computer Science and Technology, Soochow University, Suzhou, China); | |||
400 |
Open-domain Dialogue Generation Grounded with Dynamic Multi-form Knowledge Fusion
[Abstract] |
||
Feifei Xu (School of Computer Science and Technology, Shanghai University of Electric Power 201306, China); Shanlin Zhou (School of Computer Science and Technology, Shanghai University of Electric Power 201306, China); Yunpu Ma (Chair of Database Systems and Data Mining, University of Munich 80538, Munich); Xinpeng Wang (School of Electronics and Information Engineering, Tongji University 201804, China); Wenkai Zhang (School of Computer Science and Technology, Shanghai University of Electric Power 201306, China); Zhisong Li (Data Intelligence Center, Alibaba Local Life Service Co., Ltd 200062, China); | |||
158 |
Knowing What I Don’t Know: A Generation Assisted Rejection Framework in Knowledge Base Question Answering
[Abstract] |
||
Junyang Huang (Fudan University, Shanghai, China); Xuantao Lu (Fudan University, Shanghai, China); Jiaqing Liang (Fudan University, Shanghai, China); Qiaoben Bao (Fudan University, Shanghai, China); Chen Huang (CES Finance Co., Ltd., Shanghai, China); Yanghua Xiao (Fudan University, Shanghai, China); Bang Liu (Universit´e de Montr´eal, Montr´eal, Qu´ebec, Canada); Yunwen Chen (DataGrand Inc., Shanghai, China); | |||
348 |
PromptMNER: Prompt-based Entity-related Visual Clue Extraction and Integration for Multimodal Named Entity Recognition
[Abstract] |
||
Xuwu Wang (Shanghai Key Lab. of Data Science, School of Computer Science, Fudan University); Junfeng Tian (Alibaba DAMO Academy, Hangzhou, China); Min Gui (Shopee, Singapore, Singapore); Zhixu Li (Shanghai Key Lab. of Data Science, School of Computer Science, Fudan University); Jiabo Ye (East China Normal University, Shanghai, China); Ming Yan (Alibaba DAMO Academy, Hangzhou, China); Yanghua Xiao (Shanghai Key Lab. of Data Science, School of Computer Science, Fudan University); | |||
423 |
Towards Personalized Review Generation with Gated Multi-source Fusion Network
[Abstract] |
||
Hongtao Liu (State Key Laboratory of Communication Content Cognition, Beijing, China); Wenjun Wang (State Key Laboratory of Communication Content Cognition, Beijing, China); Hongyan Xu (State Key Laboratory of Communication Content Cognition, Beijing, China); Qiyao Peng (State Key Laboratory of Communication Content Cognition, Beijing, China); Pengfei Jiao (School of Cyberspace, Hangzhou Dianzi University, Hangzhou, China); Yueheng Sun (State Key Laboratory of Communication Content Cognition, Beijing, China); | |||
506 |
Definition-Augmented Jointly Training Framework for Intention Phrase Mining
[Abstract] |
||
Denghao Ma (Meituan, Beijing, China); Yueguo Chen (DEKE Lab, Renmin University of China, Beijing, China); Changyu Wang (JD.com, Inc., Beijing, China); Hongbin Pei (Xi’an Jiaotong University, Xian, China); Yitao Zhai (Meituan, Beijing, China); Gang Zheng (Meituan, Beijing, China); Qi Chen (Meituan, Beijing, China); | |||
6 |
Research Session #6 (Text and Image-II),
(April 12 (Tuesday), 2022, 14.45-16.30 , Hall 3) |
99 |
Inter- and Intra-Domain Relation-aware Heterogeneous Graph Convolutional Networks for Cross-Domain Recommendation
[Abstract] |
Ke Wang (Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China); Yanmin Zhu (Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China); Haobing Liu (Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China); Tianzi Zang (Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China); Chunyang Wang (Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China); Kuan Liu (Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China); | |||
294 |
Knowledge-Enhanced Multi-task Learning for Course Recommendation
[Abstract] |
||
Qimin Ban (School of Computer Science and Technology, East China Normal University, Shanghai, China); Wen Wu (School of Computer Science and Technology, East China Normal University, Shanghai, China); Wenxin Hu (School of Data Science and Engineering, East China Normal University, Shanghai, China); Hui Lin (Shanghai Liulishuo Information Technology Co., Ltd., Shanghai, China); Wei Zheng (Information Technology Services, East China Normal University, Shanghai, China); Liang He (School of Computer Science and Technology, East China Normal University, Shanghai, China); | |||
406 |
Joint Locality Preservation and Adaptive Combination for Graph Collaborative Filtering
[Abstract] |
||
Zhiqiang Guo (School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China); Chaoyang Wang (School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China); Zhi Li (School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China); Jianjun Li (School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China); Guohui Li ( School of Software Engineering, Huazhong University of Science and Technology, Wuhan, China); | |||
447 |
Hyperbolic Personalized Tag Recommendation
[Abstract] |
||
Weibin Zhao (State Key Lab for Novel Software Technology, Nanjing University, Nanjing, China); Aoran Zhang (Tongda college, Nanjing University of Posts and Telecommunications, Yangzhou, China); Lin Shang (State Key Lab for Novel Software Technology, Nanjing University, Nanjing, China); Yonghong Yu (Tongda college, Nanjing University of Posts and Telecommunications, Yangzhou, China); Li Zhang (Department of Computer Science, Royal Holloway, University of London, Surrey, UK); Can Wang (School of Information and Communication Technology, Griffith University, Brisbane, Australia); Jiajun Chen (State Key Lab for Novel Software Technology, Nanjing University, Nanjing, China); Hongzhi Yin (School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia); | |||
14 |
Collaborative Filtering for Recommendation in Geometric Algebra
[Abstract] |
||
Longcan Wu (Northeastern University, Shenyang, China); Daling Wang (Northeastern University, Shenyang, China); Shi Feng (Northeastern University, Shenyang, China); Kaisong Song (Northeastern University, Shenyang, China); Yifei Zhang (Northeastern University, Shenyang, China); Ge Yu (Northeastern University, Shenyang, China); | |||
397 |
SAER: Sentiment-opinion Alignment Explainable Recommendation
[Abstract] |
||
Xiaoning Zong (School of Software, Shandong University, Jinan, China); Yong Liu (Alibaba-NTU Singapore Joint Research Institute, Nanyang Technological University, Singapore); Yonghui Xu (Joint SDU-NTU Centre for Artificial Intelligence Research (C-FAIR), Shandong University, Jinan, China); Yixin Zhang (School of Software, Shandong University, Jinan, China); Zhiqi Shen (School of Computer Science and Engineering, Nanyang Technological University, Singapore); Yonghua Yang (Alibaba Group, Hangzhou, China); Lizhen Cui (School of Software, Shandong University, Jinan, China); | |||
437 |
Toward Auto-learning Hyperparameters for Deep Learning based Recommender Systems
[Abstract] |
||
Bo Sun (Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China); Di Wu (Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China); Mingsheng Shang (Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China); Yi He (Department of Computer Science, Old Dominion University, Norfolk, Virginia 23462, USA); | |||
7 |
Research Session #7 (Spatio-temporal Data),
(April 13 (Wednesday), 2022, 10.15-12.30, Hall 1) |
200 |
JS-STDGN: A Spatial-Temporal Dynamic Graph Network using JS-Graph for Traffic Prediction
[Abstract] |
Pengfei Li (Department of Computer Science and Technology, Soochow University, China); Junhua Fang (Department of Computer Science and Technology, Soochow University, China); Pingfu Chao (Department of Computer Science and Technology, Soochow University, China); Pengpeng Zhao (Department of Computer Science and Technology, Soochow University, China); An Liu (Department of Computer Science and Technology, Soochow University, China); Lei Zhao (Department of Computer Science and Technology, Soochow University, China); | |||
311 |
When Multitask Learning Make a Difference: Spatio-temporal Joint Prediction for Cellular Trajectories
[Abstract] |
||
Yuan Xu (Soochow University, Suzhou, China); Jiajie Xu (Soochow University, Suzhou, China); Junhua Fang (Soochow University, Suzhou, China); An Liu (Soochow University, Suzhou, China); Lei Zhao (Soochow University, Suzhou, China); | |||
7 |
Efficient Retrieval of Top-k Weighted Spatial Triangles
[Abstract] |
||
Ryosuke Taniguchi (Osaka University, Osaka, Japan); Daichi Amagata (Osaka University, Osaka, Japan); Takahiro Hara (Osaka University, Osaka, Japan); | |||
47 |
DIOT: Detecting Implicit Obstacles from Trajectories
[Abstract] |
||
Yifan Lei (School of Computing, National University of Singapore, Singapore); Qiang Huang (School of Computing, National University of Singapore, Singapore); Mohan Kankanhalli (School of Computing, National University of Singapore, Singapore); Anthony Tung (School of Computing, National University of Singapore, Singapore); | |||
267 |
Exploring Sub-skeleton Trajectories for Interpretable Recognition of Sign Language
[Abstract] |
||
Joachim Gudmundsson (University of Sydney, Australia); Martin P. Seybold (University of Sydney, Australia); John Pfeifer (University of Sydney, Australia); | |||
494 |
Significant Engagement Community Search on Temporal Networks
[Abstract] |
||
Yifei Zhang (National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China); Longlong Lin (National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China); Pingpeng Yuan (National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China); Hai Jin (National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China); | |||
510 |
Influence Computation for Indoor Spatial Objects
[Abstract] |
||
Yue Li (East China Normal University, Shanghai, China 51194501052@stu.ecnu.edu.cn); Guojie Ma (East China Normal University, Shanghai, China gjma@fem.ecnu.edu.cn); Shiyu Yang (Guangzhou University, Guangzhou, China syyang@gzhu.edu.cn; Liping Wang (East China Normal University, Shanghai, China lipingwang@sei.ecnu.edu.cn); Jiujing Zhang (Guangzhou University, Guangzhou, China jiujingzhang@e.gzhu.edu.cn); | |||
516 |
NavFPNet: A Unified Framework for Network Localization in GPS-free Navigation Scenarios
[Abstract] |
||
Jiazhi Ni (Localization Technology Department, Tencent Inc, Beijing, China); Xin Zhang (Localization Technology Department, Tencent Inc, Beijing, China); Beihong Jin (State Key Laboratory of Computer Sciences, Institute of Software, Chinese Academy of Sciences, Beijing, China); Fusang Zhang (State Key Laboratory of Computer Sciences, Institute of Software, Chinese Academy of Sciences, Beijing, China); Xin Li (Localization Technology Department, Tencent Inc, Beijing, China); Qiang Huang (Localization Technology Department, Tencent Inc, Beijing, China); Pengsen Wang (Localization Technology Department, Tencent Inc, Beijing, China); Xiang Li (Localization Technology Department, Tencent Inc, Beijing, China); Ning Xiao (Localization Technology Department, Tencent Inc, Beijing, China); Youchen Wang (Localization Technology Department, Tencent Inc, Beijing, China); Chang Liu (Localization Technology Department, Tencent Inc, Beijing, China); | |||
8 |
Research Session #8 (Recommendation-II),
(April 13 (Wednesday), 2022, 10.15-12.30, Hall 2) |
64 |
M^3-IB: A Memory-augment Multi-modal Information Bottleneck Model for Next-item Recommendation
[Abstract] |
Yingpeng Du (School of Software and Microelectronics, Peking University, Beijing, PR China); Hongzhi Liu (School of Software and Microelectronics, Peking University, Beijing, PR China); Zhonghai Wu (National Engineering Research Center of Software Engineering, and Key Lab of High Confidence Software Technologies (MOE), Peking University, Beijing, PR China) | |||
75 |
Fully Utilizing Neighbors for Session-based Recommendation with Graph Neural Networks
[Abstract] |
||
Xingyu Zhang (School of Computer Science and Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China); Chaofeng Sha (School of Computer Science and Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China); | |||
258 |
Enhancing Graph Convolution Network for Novel Recommendation
[Abstract] |
||
Xuan Ma (School of Computer Science, Wuhan University, Hubei, China); Tieyun Qian (School of Computer Science, Wuhan University, Hubei, China); Yile Liang (School of Computer Science, Wuhan University, Hubei, China); Ke Sun (School of Computer Science, Wuhan University, Hubei, China); Hang Yun (School of Computer Science, Wuhan University, Hubei, China); Mi Zhang (School of Computer Science, Wuhan University, Hubei, China) | |||
301 |
PMAR: Multi-Aspect Recommendation Based on Psychological Gap
[Abstract] |
||
Liye Shi (School of Computer Science and Technology, East China Normal University, Shanghai, China); Wen Wu (School of Computer Science and Technology, Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, School of Psychology and Cognitive Science, East China Normal University, Shanghai, China); Yu Ji (School of Computer Science and Technology, East China Normal University, Shanghai, China); Luping Feng (School of Data Science and Engineering, East China Normal University, Shanghai, China); Liang He (School of Computer Science and Technology, East China Normal University, Shanghai, China); | |||
133 |
Graph Neural Networks with Dynamic and Static Representations for Social Recommendation
[Abstract] |
||
Junfa Lin (School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China); Siyuan Chen (School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China); Jiahai Wang (School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China); | |||
228 |
GISDCN: A Graph-based Interpolation Sequential Recommender with Deformable Convolutional Network
[Abstract] |
||
Yalei Zang (Nanjing University of Aeronautics and Astronautics, Nanjing, China); Yi Liu (Nanjing University of Aeronautics and Astronautics, Nanjing, China); Weitong Chen (The University of Queensland, Brisbane, Australia); Bohan Li (Nanjing University of Aeronautics and Astronautics, Nanjing, China); Aoran Li (Nanjing University of Aeronautics and Astronautics, Nanjing, China); Lin Yue (The University of Queensland, Brisbane, Australia); Weihua Ma (Nanjing University of Aeronautics and Astronautics, Nanjing, China); | |||
359 |
Core Interests Focused Self-Attention for Sequential Recommendation
[Abstract] |
||
Zhengyang Ai (Institute of Information Engineering and School of Cyber Security, Chinese Academy of Sciences, Beijing, China); Shupeng Wang (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China); Siyu Jia (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China); Shu Guo (National Computer Network Emergency Response Technical Team/Coordination Center of China, Beijing, China); | |||
9 |
Research Session #9 (Applications of ML-II),
(April 13 (Wednesday), 2022, 10.15-12.30, Hall 3) |
51 |
CaSS: A Channel-aware Self-supervised Representation Learning Framework for Multivariate Time Series Classification
[Abstract] |
Yijiang Chen (School of Computer Science, Fudan University, Shanghai, China); Xiangdong Zhou (School of Computer Science, Fudan University, Shanghai, China); Zhen Xing (School of Computer Science, Fudan University, Shanghai, China); Zhidan Liu (School of Computer Science, Fudan University, Shanghai, China); Minyang Xu (School of Computer Science, Fudan University, Shanghai, China and Arcplus Group PLC, Shanghai, China); | |||
312 |
Transportation-mode Aware Travel Time Estimation via Meta-learning
[Abstract] |
||
Yu Fan (School of Computer Science and Technology, Soochow University, Suzhou, China); Jiajie Xu (School of Computer Science and Technology, Soochow University, Suzhou, China); Rui Zhou (Swinburne University of Technology, Melbourne, Australia); Chengfei Liu (Swinburne University of Technology, Melbourne, Australia); | |||
380 |
Efficient Consensus Motif Discovery of All Lengths in Multiple Time Series
[Abstract] |
||
Mingming Zhang (School of Software, Fudan University, Shanghai, China); Peng Wang (School of Computer Science, Fudan University, Shanghai, China); Wei Wang (School of Computer Science, Fudan University, Shanghai, China); | |||
459 |
LiteWSC: a Lightweight Framework for Web-Scale Spectral Clustering
[Abstract] |
||
Geping Yang (Guangdong University of Technology, Faculty of Computer, China); Sucheng Deng (University of Macau, State Key Laboratory of Internet of Things for Smart City and Department of Computer and Information Science, Macau, China); Yiyang Yang (Guangdong University of Technology, Faculty of Computer, China); Zhiguo Gong (University of Macau, State Key Laboratory of Internet of Things for Smart City and Department of Computer and Information Science, Macau, China); Xiang Chen (Sun Yat-Sen University, School of Electronics and Information Technology, China); Zhifeng Hao (Shantou University, College of Engineering, China) | |||
40 |
MetisRL: A Reinforcement Learning Approach for Dynamic Routing in Data Center Networks
[Abstract] |
||
Yuanning Gao (MoE Key Lab of Artificial Intelligence, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China); Xiaofeng Gao (MoE Key Lab of Artificial Intelligence, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China); Guihai Chen (MoE Key Lab of Artificial Intelligence, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China) | |||
128 |
Learning Evolving Concepts with Online Class Posterior Probability
[Abstract] |
||
Junming Shao (Yangtze Delta Region Institute (Huzhou) and Data Mining Lab, University of Electronic Science and Technology of China, China); Kai Wang (Yangtze Delta Region Institute (Huzhou) and Data Mining Lab, University of Electronic Science and Technology of China, China); Jianyun Lu (Data Mining Lab, University of Electronic Science and Technology of China, China and School of Artificial Intelligence and Big Data, Chongqing College of Electronic Engineering, China); Zhili Qin (Yangtze Delta Region Institute (Huzhou) and Data Mining Lab, University of Electronic Science and Technology of China, China); Qiming Wangyang (Yangtze Delta Region Institute (Huzhou) and Data Mining Lab, University of Electronic Science and Technology of China, China); Qinli Yang (Yangtze Delta Region Institute (Huzhou) and Data Mining Lab, University of Electronic Science and Technology of China, China); | |||
290 |
A Trace Ratio Maximization Method for Parameter Free Multiple Kernel Clustering
[Abstract] |
||
Yan Chen (School of Computer Science, Sichuan University, Chengdu, China); Lei Wang (School of Computer and Information Technology, Shanxi Univiersity, Taiyuan, China); Liang Du (School of Computer and Information Technology, Shanxi Univiersity, Taiyuan, China and Institute of Big Data Science and Industry, Shanxi Univiersity, Taiyuan, China); Lei Duan (School of Computer Science, Sichuan University, Chengdu, China); | |||
10 |
Research Session #10 (Algorithms-I),
(April 13 (Wednesday), 2022, 14.30-16.15, Hall 1) |
181 |
Improving Information Cascade Modeling by Social Topology and Dual Role User Dependency
[Abstract] |
Baichuan Liu (School of Data Science, Fudan University, Shanghai 200433, China); Deqing Yang (School of Data Science, Fudan University, Shanghai 200433, China); Yuchen Shi (School of Data Science, Fudan University, Shanghai 200433, China); Yueyi Wang (School of Data Science, Fudan University, Shanghai 200433, China); | |||
277 |
Mining Negative Sequential Rules from Negative Sequential Patterns
[Abstract] |
||
Chuanhou Sun (Department of Computer Science and Technology, Qilu University of Technology(Shandong Academy of Sciences), Jinan, China); Xiaoqi Jiang (Department of Computer Science and Technology, Qilu University of Technology(Shandong Academy of Sciences), Jinan, China); Xiangjun Dong (Department of Computer Science and Technology, Qilu University of Technology(Shandong Academy of Sciences), Jinan, China); Tiantian Xu (Department of Computer Science and Technology, Qilu University of Technology(Shandong Academy of Sciences), Jinan, China); Long Zhao (Department of Computer Science and Technology, Qilu University of Technology(Shandong Academy of Sciences), Jinan, China); Zhao Li (Department of Computer Science and Technology, Qilu University of Technology(Shandong Academy of Sciences), Jinan, China); Yuhai Zhao (Northeastern University, Shenyang, China); | |||
287 |
CrossIndex: Memory-Friendly And Session-Aware Index for Supporting Crossfilter in Interactive Data Exploration
[Abstract] |
||
Tianyu Xia (School of Computer Science, Fudan University and Shanghai Key Laboratory of Data Science, Shanghai, China); Hanbing Zhang (School of Computer Science, Fudan University and Shanghai Key Laboratory of Data Science, Shanghai, China); Yinan Jing (School of Computer Science, Fudan University and Shanghai Key Laboratory of Data Science, Shanghai, China); Zhenying He (School of Computer Science, Fudan University and Shanghai Key Laboratory of Data Science, Shanghai, China); Kai Zhang (School of Computer Science, Fudan University and Shanghai Key Laboratory of Data Science, Shanghai, China); X. Sean Wang (School of Computer Science, Fudan University and Shanghai Key Laboratory of Data Science and Shanghai Institute of Intelligent Electronics and Systems, Shanghai, China); | |||
489 |
Hierarchical Bitmap Indexing for Range Queries on Multidimensional Arrays
[Abstract] |
||
Luboš Krčál (Dept. of Computer Science, Czech Technical University in Prague, Czech Republic); Shen-Shyang Ho (Dept. of Computer Science, Rowan University, Glassboro, NJ, USA); Jan Holub (Dept. of Computer Science, Czech Technical University in Prague, Czech Republic); | |||
261 |
A Novel Null-invariant Temporal Measure to Discover Partial Periodic Patterns in Non-uniform Temporal Databases
[Abstract] |
||
R. Uday Kiran (The University of Aizu, Fukushima, Japan); Vipul Chhabra (IIIT-Hyderabad, Hyderabad, Telangana, India); Saideep Chennupati (IIIT-Hyderabad, Hyderabad, Telangana, India); P. Krishna Reddy (IIIT-Hyderabad, Hyderabad, Telangana, India); Minh-Son Dao (NICT, Tokyo, Japan); Koji Zettsu (NICT, Tokyo, Japan); | |||
418 |
A Two-phase Approach for Recognizing Tables with Complex Structures
[Abstract] |
||
Huichao Li (Beijing Institute of Technology, Beijing, China); Lingze Zeng (Beijing Institute of Technology, Beijing, China); Weiyu Zhang (Beijing Institute of Technology, Beijing, China); Jianing Zhang (Beijing Institute of Technology, Beijing, China); Ju Fan (Renmin University of China, Beijing, China); Meihui Zhang (Beijing Institute of Technology, Beijing, China); | |||
467 |
A Dynamic Heterogeneous Graph Perception Network with Time-Based Mini-Batch for Information Diffusion Prediction
[Abstract] |
||
Wei Fan (Heilongjiang University, Harbin, China); Meng Liu (Heilongjiang University, Harbin, China); Yong Liu (Heilongjiang University, Harbin, China); | |||
11 |
Research Session #11 (Systems),
(April 13 (Wednesday), 2022, 14.30-16.15, Hall 2) |
310 |
HEM: A Hardware-aware Event Matching Algorithm for Content-based Pub/Sub Systems
[Abstract] |
Wanghua Shi (Shanghai Jiao Tong University, Shanghai, China); Shiyou Qian (Shanghai Jiao Tong University, Shanghai, China); | |||
396 |
RotorcRaft: Scalable Follower-Driven Raft on RDMA
[Abstract] |
||
Xuecheng Qi (East China Normal University, Shanghai, China); Huiqi Hu (East China Normal University, Shanghai, China); Xing Wei (East China Normal University, Shanghai, China); Aoying Zhou (East China Normal University, Shanghai, China); | |||
545 |
Efficient Matrix Computation for SGD-based Algorithms on Apache Spark
[Abstract] |
||
Baokun Han (East China Normal University, Shanghai, China); Zihao Chen (East China Normal University, Shanghai, China); Chen Xu (East China Normal University, Shanghai, China); Aoying Zhou (East China Normal University, Shanghai, China); | |||
204 |
Parallel Pivoted Subgraph Filtering with Partial Coding Trees on GPU
[Abstract] |
||
Yang Wang (Northeastern University, China); Yu Gu (Northeastern University, China); Chuanwen Li (Northeastern University, China); | |||
317 |
Txchain: Scaling Sharded Decentralized Ledger via Chained Transaction Sequences
[Abstract] |
||
Zheng Xu (Fudan University, Shanghai, China); Rui Jiang (Fudan University, Shanghai, China); Peng Zhang (Fudan University, Shanghai, China); Tun Lu (Fudan University, Shanghai, China); Ning Gu (Fudan University, Shanghai, China); | |||
471 |
Zebra: An Efficient, RDMA-Enabled Distributed Persistent Memory File System
[Abstract] |
||
Jingyu Wang (Shanghai Jiao Tong University, Shanghai, China); Shengan Zheng (Shanghai Jiao Tong University, Shanghai, China); Ziyi Lin (Alibaba Group, Hangzhou, China); Yuting Chen (Shanghai Jiao Tong University, Shanghai, China); Linpeng Huang (Shanghai Jiao Tong University, Shanghai, China); | |||
12 |
Research Session #12 (Applications of ML-III),
(April 13 (Wednesday), 2022, 14.30-16.15, Hall 3) |
6 |
Hierarchical Attention Factorization Machine for CTR Prediction
[Abstract] |
Lianjie Long (Chongqing University, Chongqing 400044, China); Yunfei Yin (Chongqing University, Chongqing 400044, China); Faliang Huang (Chongqing University, Chongqing 400044, China); | |||
35 |
MCRF: Enhancing CTR Prediction Models via Multi-Channel Feature Refinement Framework
[Abstract] |
||
Fangye Wang (Fudan University, Shanghai, China); Hansu Gu (Seattle, United States); Dongsheng Li (Microsoft Research Asia, Shanghai, China); Tun Lu (Fudan University, Shanghai, China); Peng Zhang (Fudan University, Shanghai, China); Ning Gu (Fudan University, Shanghai, China); | |||
185 |
Semi-Supervised Graph Learning with Few Labeled Nodes
[Abstract] |
||
Cong Zhang (Beijing University of Posts and Telecommunications, China); Ting Bai (Beijing University of Posts and Telecommunications, China); Bin Wu (Beijing University of Posts and Telecommunications, China); | |||
328 |
A Deep Reinforcement Learning Based Dynamic Pricing Algorithm in Ride-hailing
[Abstract] |
||
Bing Shi (Wuhan University of Technology, China); Zhi Cao (Wuhan University of Technology, China); Yikai Luo (Wuhan University of Technology, China); | |||
87 |
InDISP: An Interpretable Model for Dynamic Illness Severity Prediction
[Abstract] |
||
Xinyu Ma (Southeast University, China); Meng Wang (Southeast University, China); Xing Liu (Central South University, China); Yifan Yang (Tencent, China); Yefeng Zheng (Tencent Jarvis Lab, China); Sen Wang (University of Queensland, Australia); | |||
249 |
Generative Adversarial Imitation Learning to Search in Branch-and-Bound Algorithms
[Abstract] |
||
Qi Wang (Fudan University, China); Suzanne V. Blackley (Harvard Medical School, Boston, USA); Chunlei Tang (Harvard Medical School, Boston, USA); | |||
373 |
Market-aware Dynamic Person-Job Fit with Hierarchical Reinforcement Learning
[Abstract] |
||
Bin Fu (Peking University, Beijing, China); Hongzhi Liu (Peking University, Beijing, China); Hui Zhao (Peking University, Beijing, China); Yao Zhu (Peking University, Beijing, China); Yang Song (BOSS Zhipin, China); Tao Zhang (BOSS Zhipin, China); Zhonghai Wu (Peking University, Beijing, China); | |||
13 |
Research Session #13 (Security),
(April 13 (Wednesday), 2022, 16.30-18.00, Hall 1) |
21 |
ADAPT: Adversarial Domain Adaptation with Purifier Training for Cross-domain Credit Risk Forecasting
[Abstract] |
Guanxiong Zeng (Alibaba Group, China.); Jianfeng Chi (Alibaba Group, China.); Rui Ma (Alibaba Group, China.); Jinghua Feng (Alibaba Group, China.); Xiang Ao (University of Chinese Academy of Sciences, Beijing, China.); Hao Yang (Alibaba Group, China.); | |||
345 |
Poisoning Attacks on Fair Machine Learning
[Abstract] |
||
Minh-Hao Van (University of Arkansas, Fayetteville, USA); Wei Du (University of Arkansas, Fayetteville, USA); Xintao Wu (University of Arkansas, Fayetteville, USA); Aidong Lu (University of North Carolina at Charlotte, USA); | |||
284 |
Bi-Level Selection via Meta Gradient for Graph-based Fraud Detection
[Abstract] |
||
Linfeng Dong (Chinese Academy of Sciences (CAS), Beijing, China); Yang Liu (Chinese Academy of Sciences (CAS), Beijing, China); Xiang Ao (Chinese Academy of Sciences (CAS), Beijing, China); Jianfeng Chi (Alibaba Group, Hangzhou, China); Jinghua Feng (Alibaba Group, Hangzhou, China); Hao Yang (Alibaba Group, Hangzhou, China); Qing He (Chinese Academy of Sciences (CAS), Beijing, China); | |||
344 |
Contrastive Learning for Insider Threat Detection
[Abstract] |
||
Vinay M.S. (University of Arkansas, Fayetteville, USA); Shuhan Yuan (University of Arkansas, Fayetteville, USA); Xintao Wu (Utah State University, Logan, USA); | |||
355 |
Metadata Privacy Preservation for Blockchain-based Healthcare Systems
[Abstract] |
||
Lixin Liu (Renmin University of China, Beijing, China); Xinyu Li (The University of Hong Kong, Hong Kong, China); Man Ho AU (The University of Hong Kong, Hong Kong, China); Zhuoya Fan (Renmin University of China, Beijing, China); Xiaofeng Meng (Renmin University of China, Beijing, China); | |||
384 |
Blockchain-Based Encrypted Image Storage and Search in Cloud Computing
[Abstract] |
||
Yingying Li (Xidian University, Xi’an, China); Jianfeng Ma (Xidian University, Xi’an, China); Yinbin Miao (Xidian University, Xi’an, China); Ximeng Liu (Fuzhou University, Fuzhou, China); Qi Jiang (Xidian University, Xi’an, China); | |||
14 |
Research Session #14 (Text and Image-III),
(April 13 (Wednesday), 2022, 16.30-18.00, Hall 2) |
223 |
Semantic-based Data Augmentation for Math Word Problems
[Abstract] |
Ailisi Li (Fudan University, Shanghai, China); Yanghua Xiao (Fudan University, Shanghai, China); Jiaqing Liang (Fudan University, Shanghai, China); Yunwen Chen (DataGrand Inc., Shanghai, China); | |||
455 |
Aligning Internal Regularity and External Influence of Multi-Granularity for Temporal Knowledge Graph Embedding
[Abstract] |
||
Tingyi Zhang (Soochow University, Suzhou, China); Zhixu Li (Fudan University, China); Jiaan Wang (Soochow University, Suzhou, China); Jianfeng Qu (Soochow University, Suzhou, China); Lin Yuan (Soochow University, Suzhou, China); An Liu (Soochow University, Suzhou, China); Lei Zhao (Soochow University, Suzhou, China); Zhigang Chen (iFLYTEK Research, Suzhou, China); | |||
518 |
FalCon: A Faithful Contrastive Framework for Response Generation in TableQA Systems
[Abstract] |
||
Shineng Fang (Fudan University, Shanghai, China); Jiangjie Chen (Fudan University, Shanghai, China); Xinyao Shen (Fudan University, Shanghai, China); Yunwen Chen (DataGrand Inc., Shanghai, China); Yanghua Xiao (Fudan University, Shanghai, China); | |||
80 |
Tipster: A Topic-Guided Language Model for Topic-Aware Text Segmentation
[Abstract] |
||
Zheng Gong (University of Science and Technology of China, Hefei, China); Shiwei Tong (University of Science and Technology of China, Hefei, China); Han Wu (University of Science and Technology of China, Hefei, China); Qi Liu (University of Science and Technology of China, Hefei, China); Hanqing Tao (University of Science and Technology of China, Hefei, China); Wei Huang (University of Science and Technology of China, Hefei, China); Runlong Yu (University of Science and Technology of China, Hefei, China); | |||
155 |
Predicting Rumor Veracity on Social Media with Graph Structured Multi-task Learning
[Abstract] |
||
Yudong Liu (Beijing University of Posts and Telecommunications,Beijing, China); Xiaoyu Yang (Beijing University of Posts and Telecommunications,Beijing, China); Xi Zhang (Beijing University of Posts and Telecommunications,Beijing, China); Zhihao Tang (Beijing University of Posts and Telecommunications,Beijing, China); Zongyi Chen (Beijing University of Posts and Telecommunications,Beijing, China); Liwen Zhang (Beijing University of Posts and Telecommunications,Beijing, China); | |||
188 |
KAAS: A Keyword-Aware Attention Abstractive Summarization Model for Scientific Articles
[Abstract] |
||
Shuaimin Li (University of Chinese Academy of Sciences, Beijing, China); Jungang Xu (University of Chinese Academy of Sciences, Beijing, China); | |||
198 |
PERM: Pre-training Question Embeddings via Relation Map for Improving Knowledge Tracing
[Abstract] |
||
Wentao Wang (Northwest Normal University, China); Huifang Ma (Northwest Normal University, China); Yan Zhao (Northwest Normal University, China); Fanyi Yang (Northwest Normal University, China); Liang Chang (Guilin University of Electronic Technology, China); | |||
15 |
Research Session #15 (Graphs-II),
(April 13 (Wednesday), 2022, 16.30-18.00, Hall 3) |
98 |
On Glocal Explainability of Graph Neural
Networks
[Abstract] |
Ge Lv (The Hong Kong University of Science and Technology, Hong Kong, China); Lei Chen (The Hong Kong University of Science and Technology, Hong Kong, China); Caleb Chen Cao (Huawei Technologies, Hong Kong, China); | |||
337 |
Temporal Network Embedding with Motif
Structural Features
[Abstract] |
||
Zhi Qiao (Beijing Key Lab of Network Technology, School of Computer Science and Engineering, Beihang University, Beijing, China); Wei Li (Beijing Key Lab of Network Technology, School of Computer Science and Engineering, Beihang University, Beijing, China); Yunchun Li (Beijing Key Lab of Network Technology, School of Computer Science and Engineering, Beihang University, Beijing, China); | |||
392 |
What affects the performance of models? Sensitivity
Analysis of Knowledge graph embedding
[Abstract] |
||
Han Yang (Peking University, Beijing, China); Leilei Zhang (Peking University, Beijing, China); Fenglong Su(National University of Defense Technology, Hunan, China); Jinhui Pang (Beijing Institute of Technology, Beijing, China); | |||
123 |
CollaborateCas: Popularity Prediction of
Information Cascades based on Collaborative
Graph Attention Networks
[Abstract] |
||
Xianren Zhang (CQU-UC Joint Co-op Institute, Chongqing University, Chongqing, China and Key Laboratory of Dependable Service Computing in Cyber Physical Society, Ministry of Education, Chongqing University, Chongqing, China); Jiaxing Shang (College of Computer Science, Chongqing University, Chongqing, China and Key Laboratory of Dependable Service Computing in Cyber Physical Society, Ministry of Education, Chongqing University, Chongqing, China); Xueqi Jia (College of Computer Science, Chongqing University, Chongqing, China and Key Laboratory of Dependable Service Computing in Cyber Physical Society, Ministry of Education, Chongqing University, Chongqing, China); Dajiang Liu (College of Computer Science, Chongqing University, Chongqing, China and Key Laboratory of Dependable Service Computing in Cyber Physical Society, Ministry of Education, Chongqing University, Chongqing, China); Fei Hao (School of Computer Science, Shaanxi Normal University, Xian, China); Zhiqing Zhang (CQU-UC Joint Co-op Institute, Chongqing University, Chongqing, China); | |||
356 |
IncreGNN: Incremental Graph Neural Network
Learning by Considering Node and Parameter
Importance
[Abstract] |
||
Di Wei (School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China); Yu Gu (School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China); Yumeng Song (School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China); Zhen Song (School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China); Fangfang Li (School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China); and Ge Yu (School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China); | |||
427 |
Representation Learning in Heterogeneous
Information Networks Based on Hyper
Adjacency Matrix
[Abstract] |
||
Bin Yang (School of Software, Fudan University, Shanghai, China); Yitong Wang (School of Software, Fudan University, Shanghai, China); | |||
16 |
Research Session #16 (Algorithms-II),
(April 14 (Thursday), 2022, 10.15-12.30, Hall 1) |
194 |
Discovering Bursting Patterns over
Streaming Graphs
[Abstract] |
Qianzhen Zhang (Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha, China) , Deke Guo (Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha, China) , and Xiang Zhao (Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha, China) | |||
327 |
GHStore: A High Performance Global Hash
based key-value store
[Abstract] |
||
Jiaoyang Li (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China and School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China) , Yinliang Yue (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China and School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China) , and Weiping Wang (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China and School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China) | |||
533 |
Membership Algorithm for Single-Occurrence
Regular Expressions with Shuffle and Counting
[Abstract] |
||
Xiaofan Wang (State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing 100190, China) | |||
10 |
(p, n)-core: core decomposition in signed networks
[Abstract] |
||
Junghoon Kim (Nanyang Technological University, 639798, Singapore) and Sungsu Lim (Chungnam National University, 34134, South Korea) | |||
120 |
TROP: Task Ranking Optimization Problem on
Crowdsourcing Service Platform
[Abstract] |
||
Jiale Zhang (MoE Key Lab of Artificial Intelligence, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China), Haozhen Lu (MoE Key Lab of Artificial Intelligence, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China) , Xiaofeng Gao (MoE Key Lab of Artificial Intelligence, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China), Ailun Song (Tencent Inc., Shenzhen, China), and Guihai Chen (Tencent Inc., Shenzhen, China) | |||
240 |
HATree: A Hotness-Aware Tree Index with
In-Node Hotspot Cache for NVM/DRAM-Based
Hybrid Memory Architecture
[Abstract] |
||
Gaocong Liu (University of Science and Technology of China, Hefei, China) , Yongping Luo (University of Science and Technology of China, Hefei, China) , Peiquan Jin (University of Science and Technology of China, Hefei, China and Key Laboratory of Electromagnetic Space Information, CAS, Hefei, China) | |||
349 |
Utilizing Expert Knowledge and Contextual
Information for Sample-limited
Causal Graph Construction
[Abstract] |
||
Xuwu Wang (Shanghai Key Lab. of Data Science, School of Computer Science, Fudan University) , Xueyao Jiang (Shanghai Key Lab. of Data Science, School of Computer Science, Fudan University) , Sihang Jiang (Shanghai Key Lab. of Data Science, School of Computer Science, Fudan University), Zhixu Li (Shanghai Key Lab. of Data Science, School of Computer Science, Fudan University), and Yanghua Xiao (Shanghai Key Lab. of Data Science, School of Computer Science, Fudan University and Fudan-Aishu Cognitive Intelligence Joint Research Center, Shanghai, China) | |||
463 |
Towards Unification of Statistical Reasoning,
OLAP and Association Rule Mining: Semantics
and Pragmatics
[Abstract] |
||
Rahul Sharma (Information Systems Group, Tallinn University of Technology, Tallinn, Estonia) , Minakshi Kaushik (Information Systems Group, Tallinn University of Technology, Tallinn, Estonia) , Sijo Arakkal Peious (Information Systems Group, Tallinn University of Technology, Tallinn, Estonia) , Mahtab Shahin (Information Systems Group, Tallinn University of Technology, Tallinn, Estonia), Amrendra Singh Yadav (Vellore Institute of Technology - VIT Bhopal, India), and Dirk Draheim (Information Systems Group, Tallinn University of Technology, Tallinn, Estonia) | |||
17 |
Research Session #17 (Recommendation-III),
(April 14 (Thursday), 2022, 10.15-12.30, Hall 2) |
300 |
Learning Social Influence from Network
Structure for Recommender Systems
[Abstract] |
Ting Bai (Beijing University of Posts and Telecommunications and Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education), Yanlong Huang (Beijing University of Posts), and Bin Wu (Beijing University of Posts and Telecommunications and Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education) | |||
398 |
Meta-path Enhanced Lightweight Graph Neural
Network for Social Recommendation
[Abstract] |
||
Hang Miao (Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, China and College of Computer Science and Technology, Jilin University, Changchun,China), Anchen Li (Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, China and College of Computer Science and Technology, Jilin University, Changchun,China) and Bo Yang (Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, China and College of Computer Science and Technology, Jilin University, Changchun,China) | |||
402 |
Multi-view Multi-behavior Contrastive Learning
in Recommendation
[Abstract] |
||
Yiqing Wu (Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS, Beijing 100190 and China University of Chinese Academy of Sciences, Beijing 100049, China and WeChat Search Application Department, Tencent, China) , Ruobing Xie (WeChat Search Application Department, Tencent, China), Yongchun Zhu (Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) and Institute of Computing Technology, CAS, Beijing 100190) , Xiang Ao(Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) and Institute of Computing Technology, CAS, Beijing 100190) , Xin Chen(WeChat Search Application Department, Tencent, China) , Xu Zhang (WeChat Search Application Department, Tencent, China) , Fuzhen Zhuang (Institute of Artificial Intelligence, Beihang University, Beijing 100191, China and Xiamen Institute of Data Intelligence, Xiamen, China) , Leyu Lin (WeChat Search Application Department, Tencent, China) , and Qing He (Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) and Institute of Computing Technology, CAS, Beijing 100190) | |||
452 |
Diffusion-based Graph Contrastive Learning for
Recommendation with Implicit Feedback
[Abstract] |
||
Lingzi Zhang, Yong Liu, Xin Zhou, Chunyan Miao, Guoxin Wang, and Haihong Tang | |||
354 |
Deep Graph Mutual Learning for Cross-domain
Recommendation
[Abstract] |
||
Yifan Wang (School of Computer Science, Peking University, Beijing, China) , Yongkang Li (School of Computer Science, Peking University, Beijing, China), Shuai Li (School of Computer Science, Peking University, Beijing, China), Weiping Song (School of Computer Science, Peking University, Beijing, China) , Jiangke Fan (Meituan) , Shan Gao (Meituan), Ling Ma (Meituan), Bing Cheng (Meituan), Xunliang Cai (Meituan), Sheng Wang (Paul G. Allen School of Computer Science, University of Washington), Ming Zhang (School of Computer Science, Peking University, Beijing, China) | |||
453 |
GELibRec: Third-Party Libraries
Recommendation Using Graph Neural Network
[Abstract] |
||
Chengming Zou (Hubei Key Laboratory of Transportation Internet of Things, Wuhan University of Technology, Wuhan, China and Peng Cheng National Laboratory, Shenzhen, China),Zhenfeng Fan (School of Computer Science and Technology, Wuhan University of Technology, Wuhan, China) | |||
18 |
Research Session #18 (Applications of ML-IV),
(April 14 (Thursday), 2022, 10.15-12.30, Hall 3) |
135 |
Temporal Knowledge Graph Entity Alignment via
Representation Learning
[Abstract] |
Xiuting Song (School of Computer and Communication Engineering, Northeastern University (Qinhuangdao), Qinhuangdao 066004, China), Luyi Bai (School of Computer and Communication Engineering, Northeastern University (Qinhuangdao), Qinhuangdao 066004, China), Rongke Liu (School of Computer and Communication Engineering, Northeastern University (Qinhuangdao), Qinhuangdao 066004, China), Han Zhang (School of Computer and Communication Engineering, Northeastern University (Qinhuangdao), Qinhuangdao 066004, China) | |||
208 |
Human Mobility Identification by Deep Behavior
Relevant Location Representation
[Abstract] |
||
Tao Sun (Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China and School of Computing Science and Technology, University of Chinese Academy of Sciences, Beijing, China), Fei Wang (Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China) , Zhao Zhang (Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China), Lin Wu (Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China), and Yongjun Xu (Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China) | |||
469 |
Dual Confidence Learning Network for
Open-World Time Series Classification
[Abstract] |
||
Junwei Lv (Key Laboratory of Knowledge Engineering with Big Data, Ministry of Education, Hefei University of Technology, Hefei 230009, China and School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230009, China), Ying He (Key Laboratory of Knowledge Engineering with Big Data, Ministry of Education, Hefei University of Technology, Hefei 230009, China and School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230009, China), Xuegang Hu (Key Laboratory of Knowledge Engineering with Big Data, Ministry of Education, Hefei University of Technology, Hefei 230009, China and School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230009, China), Desheng Cai (School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230009, China), Yuqi Chu (School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230009, China) and Jun Hu (National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China) | |||
530 |
Port Container Throughput Prediction Based on
Variational AutoEncoder
[Abstract] |
||
Jingze Li (School of Computer Science, Fudan University, Shanghai, China, Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China and Shanghai Institute of Intelligent Electronics & Systems, Fudan University, Shanghai, China) , Shengmin Shi ( School of Computer Science, Fudan University, Shanghai, China, Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China and Shanghai Institute of Intelligent Electronics & Systems, Fudan University, Shanghai, China) , Tongbing Chen (School of Computer Science, Fudan University, Shanghai, China, Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China and Shanghai Institute of Intelligent Electronics & Systems, Fudan University, Shanghai, China), Yu Tian (Shanghai International Port (Group) Co., Ltd., Shanghai, China) ,Yihua Ding (Shanghai Harbor e-logistics Software Co., Ltd., Shanghai, China), Yiyong Xiao (NeZha Smart Port&Shipping Technology (Shanghai) Co., Ltd., Shanghai, China), and Weiwei Sun (School of Computer Science, Fudan University, Shanghai, China, Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China and Shanghai Institute of Intelligent Electronics & Systems, Fudan University, Shanghai, China) | |||
150 |
Robust Dynamic Pricing in Online Markets with
Reinforcement Learning
[Abstract] |
||
Bolei Zhang (School of Computer, Nanjing University of Posts and Telecommunications Nanjing, PR China and State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, PR China) and Fu Xiao (School of Computer, Nanjing University of Posts and Telecommunications Nanjing, PR China) | |||
246 |
Multi-Memory enhanced Separation Network for
Indoor Temperature Prediction
[Abstract] |
||
Zhewen Duan (Xidian University, Xi’an, JD Intelligent Cities Research and JD iCity, JD Technology, Beijing, China) , Xiuwen Yi (Xidian University, Xi’an and JD Intelligent Cities Research) , Peng Li , Dekang Qi (Xidian University, Xi’an and JD Intelligent Cities Research and Southwest Jiaotong University, Chengdu), Yexin Li (Xidian University, Xi’an and JD Intelligent Cities Research), Haoran Xu (Xidian University, Xi’an and JD Intelligent Cities Research), Yanyong Huang (Southwestern University of Finance and Economics, Chengdu), Junbo Zhang (Xidian University, Xi’an and JD Intelligent Cities Research) , and Yu Zheng (Xidian University, Xi’an, JD Intelligent Cities Research and JD iCity, JD Technology, Beijing, China) | |||
422 |
TEALED: A Multi-Step Workload Forecasting
Approach Using Time-Sensitive EMD and Auto
LSTM Encoder-Decoder
[Abstract] |
||
Xiuqi Huang (MoE Key Lab of Artificial Intelligence, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China), Yunlong Cheng (MoE Key Lab of Artificial Intelligence, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China), Xiaofeng Gao (MoE Key Lab of Artificial Intelligence, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China), and Guihai Chen (MoE Key Lab of Artificial Intelligence, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China) | |||
19 |
Research Session #19 (Knowledge Bases),
(April 14 (Thursday), 2022, 14.30-16.15, Hall 1) |
44 |
Triple-as-Node Knowledge Graph and Its Embeddings
[Abstract] |
Xin Lv (Department of Computer Science and Technology, BNRist and KIRC, Institute for Artificial Intelligence, Tsinghua University, Beijing 100084, China), Jiaxin Shi (Department of Computer Science and Technology, BNRist and KIRC, Institute for Artificial Intelligence, Tsinghua University, Beijing 100084, China), Shulin Cao (Department of Computer Science and Technology, BNRist and KIRC, Institute for Artificial Intelligence, Tsinghua University, Beijing 100084, China), Lei Hou (Department of Computer Science and Technology, BNRist and KIRC, Institute for Artificial Intelligence, Tsinghua University, Beijing 100084, China), and Juanzi Li (Department of Computer Science and Technology, BNRist and KIRC, Institute for Artificial Intelligence, Tsinghua University, Beijing 100084, China) | |||
170 |
LeKAN: Extracting Long-tail Relations via
Layer-Enhanced Knowledge-Aggregation
Networks
[Abstract] |
||
Xiaokai Liu (National Engineering Research Center for Big Data Technology and System,Services Computing Technology and System Lab, Cluster and Grid Computing Lab and School of Cyber Science and Engineering, Huazhong University of Science and Technology, China), Feng Zhao (National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab and School of Computer Science and Technology, Huazhong University of Science and Technology, China), Xiangyu Gui (National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab and School of Computer Science and Technology, Huazhong University of Science and Technology, China), Hai Jin (National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab and School of Computer Science and Technology, Huazhong University of Science and Technology, China) | |||
264 |
TRHyTE: Temporal Knowledge Graph
Embedding based on Temporal-Relational
Hyperplanes
[Abstract] |
||
Lin Yuan (School of Computer Science and Technology, Soochow University, China), Zhixu Li (Shanghai Key Lab of Data Science, School of Computer Science, Fudan University), Jianfeng Qu (School of Computer Science and Technology, Soochow University, China), Tingyi Zhang (School of Computer Science and Technology, Soochow University, China),An Liu (School of Computer Science and Technology, Soochow University, China), Lei Zhao (School of Computer Science and Technology, Soochow University, China), and Zhigang Chen (State Key Laboratory of Cognitive Intelligence, iFLYTEK, China and iFLYTEK Research, Suzhou, China) | |||
168 |
ExKGR: Explainable Multi-hop Reasoning for
Evolving Knowledge Graph
[Abstract] |
||
Cheng Yan (National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab andSchool of Computer Science and Technology, Huazhong University of Science and Technology, China), Feng Zhao (National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab andSchool of Computer Science and Technology, Huazhong University of Science and Technology, China), Hai Jin (National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab andSchool of Computer Science and Technology, Huazhong University of Science and Technology, China) | |||
243 |
Improving Core Path Reasoning for the Weakly
Supervised Knowledge Base Question Answering
[Abstract] |
||
Nan Hu (School of Computer Science and Engineering, Southeast University, China), Sheng Bi (School of Computer Science and Engineering, Southeast University, China), Guilin Qi (School of Computer Science and Engineering, Southeast University, China), Meng Wang (School of Computer Science and Engineering, Southeast University, China), Yuncheng Hua (School of Computer Science and Engineering, Southeast University, China), and Shirong Shen (School of Computer Science and Engineering, Southeast University, China) | |||
360 |
Counterfactual-guided and Curiosity-driven
Multi-Hop Reasoning over Knowledge Graph
[Abstract] |
||
Dan Shi (Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, China and College of Computer Science and Technology, Jilin University, Changchun, China), Anchen Li (Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, China and College of Computer Science and Technology, Jilin University, Changchun, China), and Bo Yang (Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, China and College of Computer Science and Technology, Jilin University, Changchun, China) | |||
388 |
Visualizable or Non-visualizable?
Exploring the Visualizability of Concepts in
Multi-modal Knowledge Graph
[Abstract] |
||
Xueyao Jiang (Shanghai Key Laboratory of Data Science, School of Computer Science, Fudan University, Shanghai, China), Ailisi Li (Shanghai Key Laboratory of Data Science, School of Computer Science, Fudan University, Shanghai, China), Jiaqing Liang (Shanghai Key Laboratory of Data Science, School of Computer Science, Fudan University, Shanghai, China), Bang Liu (Mila & DIRO, Universit´e de Montr´eal, Montr´eal, Qu´ebec, Canada), Rui Xie (Meituan, Shanghai, China), Wei Wu (Meituan, Shanghai, China),Zhixu Li (Shanghai Key Laboratory of Data Science, School of Computer Science, Fudan University, Shanghai, China), and Yanghua Xiao (Shanghai Key Laboratory of Data Science, School of Computer Science, Fudan University, Shanghai, China and Fudan-Aishu Cognitive Intelligence Joint Research Center, Shanghai, China) | |||
20 |
Research Session #20 (Text and Image-IV),
(April 14 (Thursday), 2022, 14.30-16.15, Hall 2) |
90 |
Information Networks based Multi-semantic Data
Embedding for Entity Resolution
[Abstract] |
Chenchen Sun (School of Computer Science and Engineering, Tianjin University of Technology, Tianjin, China,Engineering Research Center of Learning-Based Intelligent System (Ministry of Education),Tianjin University of Technology, Tianjin, China and College of Intelligence and Computing, Tianjin University, Tianjin, China), Derong Shen (School of Computer Science and Engineering, Northeastern University, Shenyang, China) and Tiezheng Nie (School of Computer Science and Engineering, Northeastern University, Shenyang, China) | |||
269 |
Empowering Transformer with Hybrid Matching
Knowledge for Entity Matching
[Abstract] |
||
Wenzhou Dou (School of Computer Science and Engineering, Northeastern University,Shenyang, China), Derong Shen (School of Computer Science and Engineering, Northeastern University, Shenyang, China), Tiezheng Nie (School of Computer Science and Engineering, Northeastern University,Shenyang, China), Yue Kou (School of Computer Science and Engineering, Northeastern University,Shenyang, China), Chenchen Sun (School of Computer Science and Engineering, Tianjin University of Technology, Tianjin, China),Hang Cui (University of Illinois at Urbana-Champaign, United States), and Ge Yu (School of Computer Science and Engineering, Northeastern University,Shenyang, China) | |||
445 |
Fake Restaurant Review Detection Using Deep
Neural Networks with Hybrid Feature Fusion
Method
[Abstract] |
||
Yifei Jian (School of Cyber Science and Engineering, Sichuan University, Chengdu, China), Xingshu Chen (School of Cyber Science and Engineering, Sichuan University, Chengdu, China), and Haizhou Wang (School of Cyber Science and Engineering, Sichuan University, Chengdu, China) | |||
179 |
Medical image fusion based on pixel-level
nonlocal self-similarity prior and optimization
[Abstract] |
||
Rui Zhu (Key Laboratory of Symbolic Computation and Knowledge Engineering, Ministry of Education, Jilin University, Changchun, 130012, China and College of Computer Science and Technology, Jilin University, Changchun, 130012, China), Xiongfei Li (Key Laboratory of Symbolic Computation and Knowledge Engineering, Ministry of Education, Jilin University, Changchun, 130012, China and College of Computer Science and Technology, Jilin University, Changchun, 130012, China), Yu Wang (Key Laboratory of Symbolic Computation and Knowledge Engineering, Ministry of Education, Jilin University, Changchun, 130012, China and College of Computer Science and Technology, Jilin University, Changchun, 130012, China), and Xiaoli Zhang (Key Laboratory of Symbolic Computation and Knowledge Engineering, Ministry of Education, Jilin University, Changchun, 130012, China and College of Computer Science and Technology, Jilin University, Changchun, 130012, China) | |||
187 |
Knowledge-enhanced Interactive Matching Network for
Multi-turn Response Selection in Medical Dialogue
Systems
[Abstract] |
||
Ying Zhu (School of Computer Science and Engineering, Northeastern University, Shenyang, China), Shi Feng (School of Computer Science and Engineering, Northeastern University, Shenyang, China), Daling Wang (School of Computer Science and Engineering, Northeastern University, Shenyang, China), Yifei Zhang (School of Computer Science and Engineering, Northeastern University, Shenyang, China), Donghong Han (School of Computer Science and Engineering, Northeastern University, Shenyang, China) | |||
268 |
A Three-Stage Curriculum Learning Framework
with Hierarchical Label Smoothing for
Fine-Grained Entity Typing
[Abstract] |
||
Bo Xu (School of Computer Science and Technology, Donghua University, Shanghai, China), Zhengqi Zhang (School of Computer Science and Technology, Donghua University, Shanghai, China), Chaofeng Sha (School of Computer Science, Fudan University, Shanghai, China and Shanghai Key Laboratory of Intelligence Processing, Shanghai, China), Ming Du (School of Computer Science and Technology, Donghua University, Shanghai, China), Hui Song (School of Computer Science and Technology, Donghua University, Shanghai, China), and Hongya Wang (School of Computer Science and Technology, Donghua University, Shanghai, China) | |||
395 |
TaskSum: Task-Driven Extractive Text
Summarization for Long News Documents Based
on Reinforcement Learning
[Abstract] |
||
Moming Tang (East China Normal University), Dawei Cheng (Tongji University), Cen Chen (East China Normal University), Yuqi Liang (Seek Data Inc), Yifeng Luo (East China Normal University), and Weining Qian (East China Normal University) | |||
21 |
Research Session #21 (Recommendation-IV),
(April 14 (Thursday), 2022, 14.30-16.15, Hall 3) |
12 |
MDKE: Multi-level Disentangled Knowledge-based
Embedding for Recommender Systems
[Abstract] |
Haolin Zhou (MoE Key Lab of Artificial Intelligence,Department of Computer Science and Engineering,Shanghai Jiao Tong University, Shanghai, China), Qingmin Liu (MoE Key Lab of Artificial Intelligence,Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China), Xiaofeng Gao (MoE Key Lab of Artificial Intelligence,Department of Computer Science and Engineering,Shanghai Jiao Tong University, Shanghai, China), and Guihai Chen (MoE Key Lab of Artificial Intelligence, Department of Computer Science and Engineering,Shanghai Jiao Tong University, Shanghai, China) | |||
401 |
Intention Adaptive Graph Neural Network for
Category-aware Session-based Recommendation
[Abstract] |
||
Chuan Cui (Tongji University, Shanghai, China), Qi Shen (Tongji University, Shanghai, China), Shixuan Zhu (Tongji University, Shanghai, China), Yitong Pang (Tongji University, Shanghai, China), Yiming Zhang (Tongji University, Shanghai, China),Hanning Gao (Tongji University, Shanghai, China), and Zhihua Wei (Tongji University, Shanghai, China) | |||
430 |
Gated Hypergraph Neural Network for
Scene-aware Recommendation
[Abstract] |
||
Tianchi Yang (Beijing University of Posts and Telecommunications, China), Luhao Zhang (Meituan, China), Chuan Shi (Beijing University of Posts and Telecommunications, China), Cheng Yang (Beijing University of Posts and Telecommunications, China), Siyong Xu (Beijing University of Posts and Telecommunications, China), Ruiyu Fang (Meituan, China), Maodi Hu (Meituan, China), Huaijun Liu (Meituan, China), Tao Li (Meituan, China), Dong Wang (Meituan, China) | |||
13 |
Multi-Behavior Recommendation with
Two-Level Graph Attentional Networks
[Abstract] |
||
Yunhe Wei (College of Computer Science and Engineering, Northwest Normal University, Lanzhou Gansu 730070, China), Huifang Ma (College of Computer Science and Engineering, Northwest Normal University, Lanzhou Gansu 730070, China, Guangxi Key Lab of Multi-source Information Mining and Security, and Guangxi Normal University, Guilin Guangxi, 541004, China Guangxi Key Lab of Trusted Software, Guilin University of Electronic Technology, Guilin Guangxi, 541004, China), Yike Wang (College of Computer Science and Engineering, Northwest Normal University, Lanzhou Gansu 730070, China), Zhixin Li (Guangxi Key Lab of Multi-source Information Mining and Security, Guangxi Normal University, Guilin Guangxi, 541004, China), and Liang Chang (Guangxi Key Lab of Trusted Software, Guilin University of Electronic Technology, Guilin Guangxi, 541004, China) | |||
157 |
Toward Paper Recommendation by Jointly
Exploiting Diversity and Dynamics in
Heterogeneous Information Networks
[Abstract] |
||
Jie Wang (School of Computer Science and Technology, Soochoow University, Suzhou, China), Jinya Zhou (School of Computer Science and Technology, Soochoow University, Suzhou, China), Zhen Wu (School of Computer Science and Technology, Soochoow University, Suzhou, China), and Xigang Sun (School of Computer Science and Technology, Soochoow University, Suzhou, China) | |||
166 |
Enhancing Session-based Recommendation with
Global Context Information and Knowledge
Graph
[Abstract] |
||
Xiaohui Zhang (College of Computer Science and Engineering, Northwest Normal University, Lanzhou Gansu 730070, China), Huifang Ma (College of Computer Science and Engineering, Northwest Normal University, Lanzhou Gansu 730070, China and Guangxi Key Lab of Multi-source Information Mining and Security, Guangxi Normal University, Guilin Guangxi 541004, China), Zihao Gao (College of Computer Science and Engineering, Northwest Normal University, Lanzhou Gansu 730070, China), Zhixin Li (Guangxi Key Lab of Multi-source Information Mining and Security, Guangxi Normal University, Guilin Guangxi 541004, China), and Liang Chang (Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology, Guilin Guangxi 541004, China) |
6. Industry Sessions
Industry Session Id | Session Name | Paper ID | Paper Title |
(Date, Time, and Hall) | |||
1 |
Industry Session # 1
Advancing Recommendation Systems, (April 12 (Tuesday), 2022, 10.15-12.30 , Hall 4) |
553 |
A Joint Framework for Explainable
Recommendation with Knowledge Reasoning
and Graph Representation
[Abstract] |
Luhao Zhang (Meituan, China); Ruiyu Fang (Beijing University of Posts and Telecommunications, China); Tianchi Yang (Meituan, China); Maodi Hu (Meituan, China); Tao Li (Meituan, China); Chuan Shi (Beijing University of Posts and Telecommunications, China); Dong Wang (Meituan, China); | |||
568 |
XDM: Improving Sequential Deep Matching with Unclicked User Behaviors for Recommender System
[Abstract] |
||
Fuyu Lv (Alibaba Group, Hangzhou, China); Mengxue Li (Alibaba Group, Hangzhou, China); Tonglei Guo (Alibaba Group, Hangzhou, China); Changlong Yu (The Hong Kong University of Science and Technology, Hong Kong, China); Fei Sun (Alibaba Group, Hangzhou, China); Taiwei Jin (Alibaba Group, Hangzhou, China); Wilfred Ng (The Hong Kong University of Science and Technology, Hong Kong, China); | |||
584 |
Mitigating Popularity Bias in Recommendation via Counterfactual Inference
[Abstract] |
||
Ming He (Beijing University of Technology, Beijing, China); Changshu Li (Beijing University of Technology, Beijing, China); Xinlei Hu (Beijing University of Technology, Beijing, China); Xin Chen (Beijing University of Technology, Beijing, China); Jiwen Wang (Beijing University of Technology, Beijing, China); | |||
594 |
Efficient Dual-process Cognitive Recommender Balancing Accuracy and Diversity
[Abstract] |
||
Yixu Gao (Fudan University, Shanghai, China); Kun Shao (Huawei Noah’s Ark Lab, Beijing, China); Zhijian Duan (Peking University, Beijing, China); Zhongyu Wei (Fudan University, Shanghai, China); Dong Li (Huawei Noah’s Ark Lab, Beijing, China); Bin Wang (Huawei Noah’s Ark Lab, Beijing, China); Mengchen Zhao (Huawei Noah’s Ark Lab, Beijing, China); Jianye Hao (Huawei Noah’s Ark Lab, Beijing, China); | |||
629 |
Learning and Fusing Multiple User Interest Representations for Sequential Recommendation
[Abstract] |
||
Ming He (Beijing University of Technology, Beijing, China); Tianshuo Han (Beijing University of Technology, Beijing, China); Tianyu Ding (Beijing University of Technology, Beijing, China); | |||
2 |
Industry Session # 2
Data Management and Search, (April 13 (Wednesday), 2022, 10.15-12.30 , Hall 4) |
Invited Talk / Panel: DocLens: Digiizing healthcare documents
[Abstract]
Gaurav Aggarwal (Google); Sujoy Paul (Google); Narayan Hegde (Google); |
|
627 |
Query-Document Topic Mismatch Detection
[Abstract] |
||
Sahil Chelaramani (Microsoft); Ankush Chatterjee (Microsoft); Sonam Damani (Microsoft); Kedhar Nath Narahari (Microsoft); Meghana Joshi (Microsoft); Manish Gupta (Microsoft); Puneet Agrawal (Microsoft); | |||
561 |
Beyond QA: ‘Heuristic QA’ Strategies in JIMI
[Abstract] |
||
Shuangyong Song (JD AI Research, Beijing, China); Bo Zou (JD AI Research, Beijing, China); Jianghua Lin (JD AI Research, Beijing, China); Xiaoguang Yu (JD AI Research, Beijing, China); Xiaodong He (JD AI Research, Beijing, China); | |||
571 |
SQLG+: Efficient 𝑘-hop Query Processing on RDBMS
[Abstract] |
||
Li Zeng (Huawei Technologies Co., Ltd, China); Jinhua Zhou (Huawei Technologies Co., Ltd, China); Shijun Qin (Huawei Technologies Co., Ltd, China); Haoran Cai (Huawei Technologies Co., Ltd, China); Rongqian Zhao (Huawei Technologies Co., Ltd, China); Xin Chen (Huawei Technologies Co., Ltd, China); | |||
3 |
Industry Session # 3
Industrial Machine Learning Applications, (April 14 (Thursday), 2022, 10.15-12.30 , Hall 4) |
570 |
Modeling Long-Range Travelling Times with Big Railway Data
[Abstract] |
Wenya Sun (The University of Hong Kong); Tobias Grubenmann (University of Bonn, Germany); Reynold Cheng (The University of Hong Kong); Ben Kao (The University of Hong Kong); Waiki Ching (The University of Hong Kong); | |||
579 |
Multi-scale Time Based Stock Appreciation Ranking Prediction via Price Co-movement Discrimination
[Abstract] |
||
Ruyao Xu (East China Normal University, Shanghai, China); Dawei Cheng (Tongji University, Shanghai, China); Cen Chen (East China Normal University, Shanghai, China); Siqiang Luo (Nanyang Technological University, Singapore); Yifeng Luo (East China Normal University, Shanghai, China); Weining Qian (East China Normal University, Shanghai, China); | |||
591 |
RShield: A Refined Shield for Complex Multi-Step Attack Detection based on Temporal Graph Network
[Abstract] |
||
Weiyong Yang (Nanjing University, Nanjing, China); Peng Gao (NARI Information & Communication Technology co., ltd, Nanjing, China); Hao Huang (Nanjing University, Nanjing, 210008, China); Xingshen Wei (NARI Information & Communication Technology co., ltd, Nanjing, China); Wei Liu (NARI Information & Communication Technology co., ltd, Nanjing, China); Shishun Zhu (NARI Information & Communication Technology co., ltd, Nanjing, China); Wang Luo (NARI Information & Communication Technology co., ltd, Nanjing, China); | |||
592 |
Inter-and-Intra Domain Attention Relational
Inference for Rack Temperature Prediction in
Data Center
[Abstract] |
||
Fang Shen (Alibaba Group, China); Zhan Li (Alibaba Group, China); Bing Pan (Alibaba Group, China); Ziwei Zhang (Tsinghua University, Beijing, China); Jialong Wang (Alibaba Group, China); Wendy Zhao (Alibaba Group, China); Xin Wang (Tsinghua University, Beijing, China); Wenwu Zhu (Tsinghua University, Beijing, China); |
7. Demo and PhD Consortium Session
Date, Time, and Hall | Session Name | Paper ID | Paper Title |
April 12 (Tuesday), 2022, 13.30-14.45, Hall 1 | Demo presentations | 598 |
An Interactive Data Imputation System;
[Abstract]
Yangyang Wu (Zhejiang University); Xiaoye Miao (Zhejiang University)*; Yuchen Peng (Zhejiang University); Lu Chen (Zhejiang University); Yunjun Gao (Zhejiang University); Jianwei Yin (Zhejiang University). |
599 |
FoodChain: A Food Delivery Platform Based on Blockchain for Keeping Data Privacy;
[Abstract]
Rodrigo B Folha (Federal University of Pernambuco)*; Valéria Times (Federal University of Pernambuco); Arthur Carvalho (Miami University); André Araújo (Federal University of Alagoas); Henrique Couto (Federal University of Alagoas); Flaviano Viana (Federal University of Pernambuco). |
||
601 |
A scalable lightweight RDF knowledge retrieval system;
[Abstract]
Yuming Lin (Guilin University of Electronic Techonlogy)*; Chuangxin Fang (Guilin University of Electronic Technology). |
||
603 |
CO-AutoML: An Optimizable Automated Machine Learning System;
[Abstract]
Chunnan Wang (HIT); Hongzhi Wang (Harbin Institute of Technology)*; Xu Bo (HIT); Xintong Song (Harbin Institute of Technology); Xiangyu Shi (Harbin Institute of Technology); Yuhao Bao (Harbin Institute of Technology). |
||
604 |
OIIKM: A System for Discovering Implied Knowledge from Spatial Datasets Using Ontology;
[Abstract]
Long Wang (Guilin University Of Electronic Technology)*; Xuguang Bao (Guilin University of Electronic Technology); Liang Chang (Guilin University of Electronic Technology); Tianlong Gu (Guilin University Of Electronic Technology). |
||
608 |
IDMBS: An Interactive System to Find Interesting Co-location Patterns Using SVM;
[Abstract]
Yuxiang Zhang (Guilin University of Electronic Technology)*; Xuguang Bao (Guilin University of Electronic Technology); Liang Chang (Guilin University of Electronic Technology); Tianlong Gu (Guilin University Of Electronic Technology). |
||
609 |
A Secure Trajectory Similarity Search System;
[Abstract]
Yiping Teng (Shenyang Aerospace University)*; Fanyou Zhao (Shenyang Aerospace University); Jiayv Liu (Shenyang Aerospace University); Mengfan Zhang (Shenyang Aerospace University); Jihang Duan (Shenyang Aerospace University); Zhan Shi (Shenyang Aerospace University). |
||
612 |
Data-based Insights for the Masses: Scaling Natural Language Querying to Middleware Data;
[Abstract]
Kausik Lakkaraju (University of South Carolina)*; Vinamra Palaiya (Tantiv4); Sai Teja Paladi (University of South Carolina); Chinmayi Appajigowda (Tantiv4); Biplav Srivastava (AI Institute, University of South Carolina); Lokesh Johri (tantiv4). |
||
615 |
Identifying relevant sentences for travel blogs from Wikipedia articles;
[Abstract]
Arnav Kapoor (International Institute of Information Technology, Hyderabad)*; Manish Gupta (Microsoft). |
||
PhD Consortium presentations | 630 |
Neuro-Symbolic XAI for Computational Drug Repurposing;
[Abstract]
Martin Drancé Martin Drancé (University of Bordeaux) |
|
639 |
Leveraging Non-negative Matrix Factorization for Document Summarization;
[Abstract]
Alka Khurana (Department of Computer Science, University of Delhi). |