Topic Modeling

Yanghui Rao obtained his bachelor’s degree from the Central China Normal University in Wuhan, China; a master’s degree from the Graduate University of the Chinese Academy of Science in Beijing, China; and a PhD degree from the City University of Hong Kong in the Hong Kong SAR. He is a currently an associate professor at the School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China. Rao’s research has been published in prestigious journals and conferences, including IEEE Transactions on Knowledge and Data Engineering, ACM Transactions on Information Systems, IEEE Transactions on Cybernetics, IEEE Transactions on Neural Networks and Learning Systems, ACM Transactions on Knowledge Discovery from Data, ACL, IJCAI, EMNLP, NAACL, and COLING. His research interests lie in natural language processing and text mining, with a focus on topic modeling and unsupervised learning.Qing Li earned his BEng. degree from Hunan University in Changsha, China, and MSc and PhD degrees in computer science from the University of Southern California in Los Angeles, USA. He is a chair professor at the Hong Kong Polytechnic University, a visiting professor at the Zhejiang University, a guest professor at the University of Science and Technology of China, and an adjunct professor of the Hunan University. Li’s research interests encompass multi-modal data modeling, multimedia retrieval and management, and e-learning systems. He has authored over 500 papers in the field and is an active member of the research community, serving as a journal reviewer, programme committee chair/co-chair, and as an organizer/co-organizer of various international conferences. Dr. Li is currently the chairman of the Hong Kong Web Society, a councilor of the Database Society of Chinese Computer Federation, and a steering committee member of the international WISE Society. He is a fellow of IEEE, AAIA, and IET.

• Chapter 1. Introduction.- Chapter 2. Classical Topic Models.- Chapter 3. Modern Topic Models.- Chapter 4. Applications.- Chapter 5. Discussions.