Toward the exploitation of social access patterns for recommendation

Jill Freyne, Rosta Farzan, Maurice Coyle
2007 Proceedings of the 2007 ACM conference on Recommender systems - RecSys '07  
The size and diversity of the Web has been the root cause of the poor performance of many retrieval systems, with little navigational support provided by many large online information repositories. The online information retrieval process across different repositories shares similarities with content access facilities and user behaviors even when containing inherently different content types. In this work, we introduce our social recommender system called ASSIST. The recommendation framework in
more » ... ASSIST can be applied to any online information retrieval service with key information access components, search and browsing. ASSIST exploits multiple forms of social implicit feedback in order to generate well-informed user recommendations in the online information retrieval domain.
doi:10.1145/1297231.1297266 dblp:conf/recsys/FreyneFC07 fatcat:36vqyaac6zeatojkhhxvwt5mru