时间：2017年3月9日（周四）下午14:30-15:30

地点：深圳大学科技楼1303会议室

主讲嘉宾：Dr. Chi Ho Bill Yeung The Education University of Hong Kong

杨志豪 香港教育大学

报告摘要: Recommender systems are present in many web applications to guide purchase choices. They increase sales and benefit sellers, but whether they benefit customers by providing relevant products remains less explored. While in many cases the recommended products are relevant to users, in other cases customers may be tempted to purchase the products only because they are recommended. Here we introduce a model to examine the benefit of recommender systems for users, and find that recommendations from the system can be equivalent to random draws if one always follows the recommendations and seldom purchases according to his or her own preference. Nevertheless, with sufficient information about user preferences, recommendations become accurate and an abrupt transition to this accurate regime is observed for some of the studied algorithms. On the other hand, we find that high estimated accuracy indicated by common accuracy metrics is not necessarily equivalent to high real accuracy in matching users with products. This disagreement between the estimated and the real accuracy serves as an alarm for operators and researchers who evaluate recommender systems merely with accuracy metrics. We tested our model with a real dataset and observed similar behaviors. Finally, a recommendation approach with improved accuracy is suggested. These results imply that recommender systems can benefit users, but the more frequently a user purchases the recommended products, the less relevant the recommended products in matching the user taste.

主讲人简介：Dr. Yeung, Chi Ho Bill (楊志豪) received a BSc, an MPhil, and a PhD degree in Physics from the Hong Kong University of Science and Technology (HKUST, 香港科技大學). He then worked as a postdoctoral research fellow in University of Fribourg in Switzerland and Aston University in the United Kingdom for 4 years. He is currently an Assistant Professor at the Education University of Hong Kong (EdUHK, 香港教育大學). His major research interests include disordered systems, optimization, transportation networks, recommendation systems, complex and social networks, statistical physics, and the application of information technology in education.

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