Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Content-boosted collaborative filtering for improved recommendations
Eighteenth national conference on Artificial intelligence
The Journal of Machine Learning Research
The Journal of Machine Learning Research
Proceedings of the thirteenth ACM international conference on Information and knowledge management
A maximum entropy web recommendation system: combining collaborative and content features
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Modeling relationships at multiple scales to improve accuracy of large recommender systems
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Bayesian probabilistic matrix factorization using Markov chain Monte Carlo
Proceedings of the 25th 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
Scalable Collaborative Filtering with Jointly Derived Neighborhood Interpolation Weights
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
Modeling hidden topics on document manifold
Proceedings of the 17th ACM conference on Information and knowledge management
Collaborative Filtering for Implicit Feedback Datasets
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
One-Class Collaborative Filtering
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Regression-based latent factor models
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
fLDA: matrix factorization through latent dirichlet allocation
Proceedings of the third ACM international conference on Web search and data mining
Generalized Probabilistic Matrix Factorizations for Collaborative Filtering
ICDM '10 Proceedings of the 2010 IEEE International Conference on Data Mining
Collaborative topic modeling for recommending scientific articles
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Cost-aware travel tour recommendation
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Social contextual recommendation
Proceedings of the 21st ACM international conference on Information and knowledge management
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We study the problem of recommending scientific articles to users in an online community and present a novel matrix factorization model, the topic regression Matrix Factorization (tr-MF), to solve the problem. The main idea of tr-MF lies in extending the matrix factorization with a probabilistic topic modeling. Instead of regularizing item factors through the probabilistic topic modeling as in the framework of the CTR model, tr-MF introduces a regression model to regularize user factors through the probabilistic topic modeling under the basic hypothesis that users share the similar preferences if they rate similar sets of items. Consequently, tr-MF provides interpretable latent factors for users and items, and makes accurate predictions for community users. Specifically, it is effective in making predictions for users with only few ratings or even no ratings, and supports tasks that are specific to a certain field, neither of which is addressed in the existing literature. Further, we demonstrate the efficacy of tr-MF on a large subset of the data from CiteULike, a bibliography sharing service dataset. The proposed model outperforms the state-of-the-art matrix factorization models with a significant margin.