TY - GEN
T1 - Tutorial on social recommender systems
AU - Guy, Ido
N1 - Publisher Copyright:
© Copyright 2014 by the International World Wide Web Conferences Steering Committee.
PY - 2014/4/7
Y1 - 2014/4/7
N2 - 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.
AB - 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.
KW - Recommender systems
KW - Social media
KW - Social networks
KW - Social recommender systems
KW - Social web
KW - Web 2.0
UR - http://www.scopus.com/inward/record.url?scp=84991013947&partnerID=8YFLogxK
U2 - 10.1145/2567948.2577269
DO - 10.1145/2567948.2577269
M3 - Conference contribution
AN - SCOPUS:84991013947
T3 - WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web
SP - 195
EP - 196
BT - WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web
PB - Association for Computing Machinery, Inc
T2 - 23rd International Conference on World Wide Web, WWW 2014
Y2 - 7 April 2014 through 11 April 2014
ER -