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HONG KONG BAPTIST UNIVERSITY
FACULTY OF SCIENCE

Department of Computer Science Seminar
2017 Series

User Novelty Driven Personalized Item Recommendation

Dr. Jun Chen
Senior Software Engineer
AI Group
Baidu Inc.
China

Date: December 1, 2017 (Friday)
Time: 10:30 - 11:30 am
Venue: FSC703, Fong Shu Chuen Library, Ho Sin Hang Campus

Abstract
Temporal item recommendation is crucial for many online personalized services such as music and location recommendation. Meanwhile, user novelty measures how much the active user is willing to accept unfamiliar things in real time. The main topic of this talk is about how AI technologies can be applied to analyze user novelty and further facilitate the improvement of personalized temporal item recommendation.

Biography
Dr. Jun Chen holds a Ph.D. degree and a B.Eng. degree in Software Engineering both from Tsinghua University. He has broad research interests in machine learning and data mining, especially in recommender systems. His first-authored research papers have been published in the top ranked venues like IEEE TKDE, IEEE TIP, AAAI, ACM Multimedia and KAIS. In 2017, he has won the outstanding Ph.D. graduate of Tsinghua University and that of Beijing city as well as the outstanding Ph.D. dissertation of Tsinghua University.

********* ALL INTERESTED ARE WELCOME ***********
(For enquiry, please contact Computer Science Department at 3411 2385)

http://www.comp.hkbu.edu.hk/v1/?page=seminars&id=444
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Department of Computer Science, Hong Kong Baptist University
Hong Kong Baptist University