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    供稿:数理与统计学院     
     主题:Temporal Community Mining, Computation and its Applications

  时间:2022年9月28日(周三)14:00-15:30

  方式:腾讯会议(会议号:824 121 087)  

     主办单位:数理与统计学院

     主讲人:Dr Jianxin Li is a Professor of Data Science in the School of IT, Deakin University. His research interests include social computing, query processing and optimization, and big data analytics. He has published 130 high quality research papers in top international conferences and journals, including SIGMOD, PVLDB, ICDE, ACM WWW, SIGKDD, ACM CIKM, IEEE TKDE, TII, IS, etc. His professional service can be identified by different roles in academic committees, e.g., Editor-in-Chief in Array Journal, Associate Editors in Knowledge-based Systems, World Wide Web Journal, IEEE Signal Processing Letters, Information Systems; the PC co-chairs in DASFAA 2023, WISA 2022, BESC 2022, ADMA 2019; the General co-chairs in IEEE ISPA-2020, CIT-2021; guest editors and invited reviewers in many top international journals and technical program committee members in most world leading database and data mining international conferences like PVLDB, ICDE, WSDM, ICDM, AAAI, IJCAI.

  讲座摘要:Searching for local and global communities is an important research problem that supports advanced data analysis in various complex networks, such as social networks, collaboration networks, cellular networks, etc. The evolution of such networks over time has motivated several recent studies to identify temporal communities in dynamic networks. At this talk, Prof Jianxin Li will first provide a big picture to overview the diversified types of communities investigated in recent years. After that, he will introduce a set of representative works focusing on temporal community mining, efficient computational algorithms, and the emerging applications to be supported. Furthermore, he will share his team’s recent paper accepted by PVLDB 2022 – “reliable community search in dynamic networks”. In this work, the authors proposed a novel (s, k)-core reliable community (CRC) model in the weighted dynamic networks, and defined the problem of most reliable community search that couples the desirable properties of connection strength, cohesive structure continuity, and the maximal member engagement. By taking this as an example, Prof Jianxin Li will discuss some new types of temporal communities that should pay more attention in the near future. The main goal of this talk is to help audiences to know and understand the different applications of community discovery in need, how the community models are devised, the existing research challenges and the state-of-the-arts in this topic. This talk is suitable to broad audiences who have interest in database, social data analytics, data mining and AI-driven decision making.

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