Projected gradient methods for linearly constrained problems
Mathematical Programming: Series A and B
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Proceedings of the 10th international conference on Intelligent user interfaces
IEEE Transactions on Knowledge and Data Engineering
Fast maximum margin matrix factorization for collaborative prediction
ICML '05 Proceedings of the 22nd international conference on Machine learning
Factorization meets the neighborhood: a multifaceted collaborative filtering model
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Mixed Membership Stochastic Blockmodels
The Journal of Machine Learning Research
Learning to recommend with social trust ensemble
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Trust based recommender system for the semantic web
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Use of social network information to enhance collaborative filtering performance
Expert Systems with Applications: An International Journal
Recommender systems with social regularization
Proceedings of the fourth ACM international conference on Web search and data mining
Like like alike: joint friendship and interest propagation in social networks
Proceedings of the 20th international conference on World wide web
Modeling user's receptiveness over time for recommendation
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Making recommendations from multiple domains
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Social recommendation incorporating topic mining and social trust analysis
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Incorporating social actions into recommender systems
WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
iGSLR: personalized geo-social location recommendation: a kernel density estimation approach
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Celebrity recommendation with collaborative social topic regression
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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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. In this paper, we develop a joint personal and social latent factor (PSLF) model for social recommendation. Specifically, it combines the state-of-the-art collaborative filtering and the social network modeling approaches for social recommendation. Especially, the PSLF extracts the social factor vectors for each user based on the state-of-the-art mixture membership stochastic blockmodel, which can explicitly express the varieties of the social relationship. To optimize the PSLF model, we develop a scalable expectation-maximization (EM) algorithm, which utilizes a novel approximate mean-field technique for fast expectation computation. We compare our approach with the latest social recommendation approaches on two real datasets, Flixter and Douban (both with large social networks). With similar training cost, our approach has shown a significant improvement in terms of prediction accuracy criteria over the existing approaches.