TY - GEN
T1 - Social recommender system tutorial
AU - Guy, Ido
AU - Geyer, Werner
N1 - Publisher Copyright:
Copyright © 2014 ACM.
PY - 2014/10/6
Y1 - 2014/10/6
N2 - In recent years, with the proliferation of the social web, users are increasingly exposed to social overload and the designers of social web sites are challenged to attract and retain their user basis. Social recommender systems are becoming an integral part of virtually any leading website, playing a key factor in its success: First, they aim to address the overload problem by helping users to find relevant content. Second, they can provide recommendations for content creation, increasing participation and user retention. In this tutorial, we will review the broad domain of social recommender systems, their application for the social web, the underlying techniques and methodologies; the data in use, recommended entities, and target population; evaluation techniques; and open issues and challenges.
AB - In recent years, with the proliferation of the social web, users are increasingly exposed to social overload and the designers of social web sites are challenged to attract and retain their user basis. Social recommender systems are becoming an integral part of virtually any leading website, playing a key factor in its success: First, they aim to address the overload problem by helping users to find relevant content. Second, they can provide recommendations for content creation, increasing participation and user retention. In this tutorial, we will review the broad domain of social recommender systems, their application for the social web, the underlying techniques and methodologies; the data in use, recommended entities, and target population; evaluation techniques; 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=84908884370&partnerID=8YFLogxK
U2 - 10.1145/2645710.2645778
DO - 10.1145/2645710.2645778
M3 - Conference contribution
AN - SCOPUS:84908884370
T3 - RecSys 2014 - Proceedings of the 8th ACM Conference on Recommender Systems
SP - 403
EP - 404
BT - RecSys 2014 - Proceedings of the 8th ACM Conference on Recommender Systems
PB - Association for Computing Machinery
T2 - 8th ACM Conference on Recommender Systems, RecSys 2014
Y2 - 6 October 2014 through 10 October 2014
ER -