Personalized recommendation of social software items based on social relations
作者： Ido Guy , Naama Zwerdling , David Carmel , Inbal Ronen , Erel Uziel
关键词:
摘要: We study personalized recommendation of social software items, including bookmarked web-pages, blog entries, and communities. focus on recommendations that are derived from the user's network. Social network information is collected aggregated across different data sources within our organization. At core research a comparison between based familiarity his/her similarity also examine effect adding explanations to each recommended item show related people their relationship user item. Evaluation, an extensive survey with 290 participants field 90 users, indicates superiority as basis for recommendations. In addition, important instant found - interest rate in items increases when provided.
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