Lecture Title: Knowledge-Induced Multi-Kernel Fuzzy Clustering

Lecturer: Professor Tang Yiming

Affiliation: Hefei University of Technology

Lecture Time: October 21, 2023 (Saturday) 14:30-18:00

Lecture Location: Room 1106, Science and Education Building A, Emerald Lake Campus

Lecture Abstract:

The introduction of domain knowledge has opened up a new field for fuzzy clustering, resulting in knowledge-driven and data-driven fuzzy clustering methods. To solve the problems of imperfect extraction mechanism and imperfect fusion mode in these methods, we propose a Knowledge-Induced Multi-Kernel Fuzzy Clustering (KMKFC) algorithm. Firstly, to better extract knowledge points, a Relative Density-based Knowledge Extraction (RDKE) method is proposed to extract high-density knowledge points close to the cluster centers of the real data structure and provide initial cluster centers; the introduction of a multi-kernel mechanism maps data to high-dimensional space, which can improve the adaptability of the clustering algorithm, better discover the differences between data, and obtain better clustering results. Secondly, the knowledge points generated by RDKE are integrated into KMKFC through the knowledge influence matrix, guiding the iterative process of KMKFC. Again, a strategy for automatically obtaining knowledge points is proposed, including the RDKE Automatic Knowledge Acquisition method (RDKE-A) and the corresponding KMKFC-A algorithm. The convergence of KMKFC and KMKFC-A is proved. Finally, experimental research shows that KMKFC and KMKFC-A algorithms are superior to related comparison algorithms in multiple evaluation indicators and convergence speed.

Lecturer Introduction:

Tang Yiming, a professor at Hefei University of Technology, is the deputy director of the Department of Intelligent Science and Technology. He is a standing member of the Artificial Intelligence Logic Professional Committee of the Chinese Artificial Intelligence Society, a standing member of the Non-classical Logic and Computing Professional Committee of the Chinese Logic Society, a deputy director of the Trustworthy Artificial Intelligence Professional Committee of the Anhui Artificial Intelligence Society, an executive member of the Collaborative Computing Professional Committee of the Chinese Computer Society, a member of the Machine Learning Professional Committee of the Chinese Artificial Intelligence Society, a member of the Granular Computing and Knowledge Discovery Professional Committee of the Chinese Artificial Intelligence Society, a member of the Artificial Intelligence Foundation Professional Committee of the Chinese Artificial Intelligence Society, a senior member of IEEE, a senior member of the Chinese Computer Society, and a senior member of the Chinese Artificial Intelligence Society. His main research areas involve clustering theory, collaborative computing, fuzzy reasoning, serving emotional computing, image processing, granular computing, etc. He has published more than 90 papers, including 2 ESI hotspot papers and 2 ESI highly cited papers, obtained 5 national authorized invention patents and 12 national software copyright registrations. He serves as an editorial board member of several SCI journals such as Information Sciences, a PC Member of more than 10 conferences such as AAAI, and a reviewer of more than 50 SCI journals such as TPAMI. He serves as the Paper Recommendation Chair of ChineseCSCW, the Publication Chair of FSDM 2023 International Conference, and the Publication Chair of AILA 2023 International Conference. He won the Outstanding Associate Editor of IEEE Access in 2021 and 2022. He has presided over more than 10 scientific research projects including the National Natural Science Foundation of China (3 items), the China Postdoctoral Science Foundation Special Support Project, the China Postdoctoral Science Foundation Surface Project, and the Anhui Provincial Natural Science Foundation Surface Project. He has participated in more than 20 scientific research projects such as the National Key R&D Project, the National Natural Science Foundation Key Project, and the 863 Project.