In recent years, with the proliferation of the social web, users are exposed to an intensively growing social overload. Social recommender systems aim to address this overload and are becoming integral part of virtually any leading website, playing a key factor in its success. In this tutorial, we will review the broad domain of social recommender systems, the underlying techniques and methodologies; the data in use, recommended entities, and target population; evaluation techniques; applications; and open issues and challenges.
Korean Institute of Information Scientists and Engineers
Business Registration Number : 114-82-03170
Name of Company : Korean Institute of Information Scientists and Engineers
Name of Representative : Jeong Yeon Seo
Address : 76, Bangbae-ro, Seocho-gu, Seoul, Korea
ⓒ 2014 23rd International World Wide Web Conference l WWW2014 l Seoul (Korea) l April 7 - 11, 2014
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