Personalized social search based on the user's social network

This work investigates personalized social search based on the user’s social relations – search results are re-ranked according to their relations with individuals in the user’s social network. We study the effectiveness of several social network types for personalization: (1) Familiarity-based network of people related to the user through explicit familiarity connection; (2) Similarity-based network of people “similar” to the user as reflected by their social activity; (3) Overall network that provides both relationship types. For comparison we also experiment with Topic-based personalization that is based on the user’s related terms, aggregated from several social applications. We evaluate the contribution of the different personalization strategies by an off-line study and by a user survey within our organization. In the off-line study we apply bookmark-based evaluation, suggested recently, that exploits data gathered from a social bookmarking system to evaluate pe...

• Type: Conference
• Year: 2009
• Where: CIKM
• Authors: David Carmel, Naama Zwerdling, Ido Guy, Shila Ofek-Koifman, Nadav Har'El, Inbal Ronen, Erel Uziel, Sivan Yogev, Sergey Chernov
• Keywords: CIKM 2009, Database, Social, Social Network, User Survey