【学术报告】User Experience and Technology Acceptance Issues in Recommender Systems

发稿时间:2010-05-17浏览次数:3870

题目:User Experience and Technology Acceptance Issues in Recommender Systems

报告人:Dr. Pearl PU
        Director of Human Computer Interaction Group
        Faculty of Information and Communication Sciences
        Swiss Federal Institute of Technology, Lausanne, Switzerland

时间:5月18日 14:40-15:40

地点:蒙民伟楼404会议室

摘要:As online stores offer practically an infinite shelf space, recommender
systems are playing an increasingly important role in helping users *search*
and *discover* items that they may want to buy. In this talk, I first start
with a brief survey of the rating based social recommender systems and their
applications in online industry. I will then spend some time discussing some
of the unsolved issues, especially concerning user adoption problems such as
the cold start phenomena, users' acceptance of recommendations, and
personalization. The main part of the talk focuses on the technology behind
critiquing based recommender (CBR) systems. Even though they may not address
all of the user issues, CBR systems offer some effective solutions. They do
not require users to leave traces of their interests via behavioral patterns.
Instead, they encourage users to express them via the interface. Moreover,
since users are completely involved in the preference elicitation process in
such systems, users feel more in control of the recommendation process, and as
 a consequence they are more convinced of the products recommended to them. I
will finish the talk by explaining the baggage carousel phenomenon and show
you how critiquing based recommender systems enable users find personalized
items without expending extra interaction effort. Through the analysis of some
 of our empirical studies, I hope to reveal to you some insights on the
effective design of recommender systems for scalable user adoption.

简介:Dr. Pearl Pu is the director of the Human Computer Interaction Group in
the School of Computer and Communication Sciences at the Swiss Federal
Institute of Technology in Lausanne. Her research interests include decision
support, electronic commerce, online consumer decision behavior, product
recommender systems, travel planning tools, trust-inspiring interfaces for
recommender agent, music recommenders, scalable user experience, and social
navigation. She has been recently elected as the general chair for the ACM
international conference on Recommender Systems (Recsys 2008) and ACM
international conference on Intelligent User Interfaces (IUI 2011), and
program co-chair of the ACM international conference in Electronic Commerce (E
C 2009) and Adaptive Hypermedia and Adaptive Web-Based Systems (AH 2008).She
is an associate editor of IEEE Transactions on Multimedia. She obtained her
Master and Ph.D. degrees from the University of Pennsylvania in artificial
intelligence and computer graphics. She was a visiting scholar at Stanford
University in 2001, both in the database and HCI groups.