IEEE Transactions on Knowledge and Data Engineering
Factorization meets the neighborhood: a multifaceted collaborative filtering model
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Learning to recommend with social trust ensemble
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Latent dirichlet allocation for tag recommendation
Proceedings of the third ACM conference on Recommender systems
TagiCoFi: tag informed collaborative filtering
Proceedings of the third ACM conference on Recommender systems
Analysis of cold-start recommendations in IPTV systems
Proceedings of the third ACM conference on Recommender systems
fLDA: matrix factorization through latent dirichlet allocation
Proceedings of the third ACM international conference on Web search and data mining
A survey of collaborative filtering techniques
Advances in Artificial Intelligence
A Framework of Hybrid Recommendation System for Government-to-Business Personalized E-Services
ITNG '10 Proceedings of the 2010 Seventh International Conference on Information Technology: New Generations
Information Sciences: an International Journal
Exploiting user interests for collaborative filtering: interests expansion via personalized ranking
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Recommender systems with social regularization
Proceedings of the fourth ACM international conference on Web search and data mining
Learning to recommend with explicit and implicit social relations
ACM Transactions on Intelligent Systems and Technology (TIST)
Like like alike: joint friendship and interest propagation in social networks
Proceedings of the 20th international conference on World wide web
Collaborative competitive filtering: learning recommender using context of user choice
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
International Journal of Intelligent Systems
TV program recommendation for groups based on muldimensional TV-anytime classifications
IEEE Transactions on Consumer Electronics
A trust-semantic fusion-based recommendation approach for e-business applications
Decision Support Systems
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In recent years, we have witnessed the explosive growth of microblogging services. As a popular platform for users to communicate and share information with friends, microblog has opened up new opportunities for recommendation. In this paper, we explore the possibility of recommending TV programs with microblogs. In particular, we leverage the following two important features of microblogs: (1) the rich user generated content reveals users' preferences on TV programs as well as the properties of TV programs and (2) the social interactions of the users suggest the mutual influences among the users. Taking into consideration of the above two properties, we proposed a hybrid recommendation model based on probabilistic matrix factorization, a popular collaborative filtering method. Two regularizers are added during matrix factorization: the social regularizer and the item similarity regularizer. We validate the proposed algorithm with Sina Weibo data set for TV program recommendation. The experimental results show that the proposed algorithm significantly outperforms the state-of-the-art collaborative filtering method, demonstrating the importance of incorporating social trust and item similarity in recommendation. In addition, we show that the proposed method is robust in recommending to new users, a typical cold-start scenario.