Biography:

Professor Jianxin Li is the lab director of smart networks, working in the School of IT, Deakin University. His research interests include social computing, query processing and optimization, and big data analytics. He has published 90 high quality research papers in top international conferences and journals, including PVLDB, IEEE ICDE, ACM WWW, AAAI, IEEE ICDM, EDBT, ACM CIKM, IEEE TKDE, The VLDB Journal, IEEE TII, and WWW Journal. His professional service can be identified by different roles in academic committees, e.g., the technical program committee members in ACM SIGMOD, PVLDB, AAAI, PAKDD, IEEE ICDM, and ACM CIKM; the journal reviewer in IEEE TKDE, ACM TKDD, WWW Journal and VLDB Journal; the proceeding chairs in DASFAA 2018, ADMA 2016 and ADC 2015; and the program committee chair in ADMA 2019, and the International Workshop on Social Computing 2017 and 2018; the tutorial chair in the 26th International Conference on WWW 2017; and the guest editors in international journals, such as IEEE Transactions on Industrial Informatics, Computational Intelligence, IET Intelligent Transport Systems, Complexity, Data Science and Engineering.

Speech title: Anchored Vertex Exploration for Community Engagement in Social Networks

Abstract:
User engagement has recently received significant attention in understanding decay and expansion of communities in social networks. However, the problem of user engagement hasn’t been fully explored in terms of users’ specific interests and structural cohesiveness altogether. Therefore, in this talk, the presenter will introduce one of his recent works published in IEEE ICDE 2020. It filled the gap by investigating the problem of community engagement from the perspective of attributed communities. Given a set of keywords W, a structure cohesive parameter k, and a budget parameter l, the objective is to find l number of users who can induce a maximal expanded community. Meanwhile, every community member must contain the given keywords in W and the community should meet the specified structure cohesiveness constraint k. This problem was formalised as best-Anchored Vertex set Exploration (AVE).
To solve the AVE problem, a Filter-Verify framework was developed by maintaining the intermediate results using multiway tree, and probe the best anchored users in a best search way. To accelerate the efficiency, they further design a keyword-aware anchored and follower index, and also develop an index-based efficient algorithm. The proposed algorithm can greatly reduce the cost of computing anchored users and their followers. Additionally, they present two bound properties that can guarantee the correctness of the solution. Finally, they demonstrate the efficiency of the proposed algorithms and index, as well as the effectiveness of attributed community-based community engagement model using five real-world datasets.