Learning personal + social latent factor model for social recommendation
Published 12 August 2012
Yelong Shen, Ruoming Jin
Citations99
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TL;DR
This paper develops a joint personal and social latent factor (PSLF) model that combines the state-of-the-art collaborative filtering and the social network modeling approaches for social recommendation and shows a significant improvement in terms of prediction accuracy criteria over the existing approaches.
Abstract
Social recommendation, which aims to systematically leverage the social relationships between users as well as their past behaviors for automatic recommendation, attract much attention recently. The belief is that users linked with each other in social networks tend to share certain common interests or have similar tastes (homophily principle); such similarity is expected to help improve the recommendation accuracy and quality. There have been a few studies on social recommendations; however, they almost completely ignored the heterogeneity and diversity of the social relationship.
Keywords
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