Recommendation Boosting: New Perspectives
报 告 人：杨海钦 博士
主 持 人：潘微科 博士
日 期：2016年4月22日
时 间：早上
BIOGRAPHY
Dr. Haiqin Yang is currently a postdoctoral fellow at the Chinese University of Hong Kong and will join Hang Seng Management College as an Assistant Professor on July, 2016. He received the B.Sc. degree in computer science from Nanjing University, China and the M.Phil. and Ph.D. degrees from The Chinese University of Hong Kong. His research interests include machine learning and big data analytics. In these areas, he has published two books, over thirty refereed journal and conference papers, which are scored over 2000 citations with an H-index of 18 from Google Scholar. He has initiated and successfully organized five international workshops in the topics of Scalable Data Analytics and Scalable Machine Learning. He has served as an associate editor of Neurocomputing, a program committee member of international conferences, including AAAI, AISTAT, ACML, CIKM, IEEE BigData, and a reviewer of over ten prestigious journals. http://appsrv.cse.cuhk.edu.hk/~hqyang/
ABSTRACT
Nowadays, information overload becomes a critical issue for people's daily life. To tackle this problem, recommender system is proposed and is promising to provide favorite personalized recommendation or services. Collaborative filtering (CF) techniques, making prediction of users' preference based on users' previous behaviors, have become one of the most successful technologies to build modern recommender systems. This talk will address several issues of recent CF techniques and propose new models and algorithms to improve the efficiency and effectiveness.
