Clustering Ensemble and Applications on Big Data Abstract


Clustering ensembles have emerged as a powerful method for improving both the quality and the robustness of the clustering by aggregating multiple clustering solutions into a single one. In some application domains, the supervised information can be collected automatically along with the unlabeled data. So incorporating limited supervision information into clustering ensemble may obtain user-desired and more accurate partitions. This seminar presents some recent algorithm developments in clustering ensemble, semi-supervised clustering ensemble, and their applications on big data.


Prof. Yan Yang
Southwest Jiaotong University, China

Date & Time

10 Oct 2014 (Friday) 14:30 - 15:30


E11-3033 (University of Macau)

Organized by

Department of Computer and Information Science


Dr. Yan Yang is Professor at Southwest Jiaotong University. She received her PhD degree in Traffic Information Engineering and Control in 2007 from Southwest Jiaotong University. From 2002-2003, she was with Waterloo University, Canada, as a visiting scholar. Prof. Yang’s research interests are in computational intelligence, data mining, ensemble learning, etc. She acts as the principle investigator for several high-level projects, such as NSFC projects, National Key Technology R&D, etc. She has published more than 100 research papers on high-quality journals and conferences. She also serves as the Vice Chair of ACM Chengdu Chapter, Executive Member of the CCF Chengdu Member Center, Deputy Secretary General of Sichuan Province Computer Society, Member of IEEE-CS, Senior Member of CCF and CAI.