Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Automatic image annotation and retrieval using cross-media relevance models
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Collaborative filtering via gaussian probabilistic latent semantic analysis
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
The Journal of Machine Learning Research
The Journal of Machine Learning Research
Automatic multimedia cross-modal correlation discovery
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
IEEE Transactions on Knowledge and Data Engineering
Modeling Semantic Aspects for Cross-Media Image Indexing
IEEE Transactions on Pattern Analysis and Machine Intelligence
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Relational learning via collective matrix factorization
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Transfer learning for collaborative filtering via a rating-matrix generative model
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
On social networks and collaborative recommendation
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Fast nonparametric matrix factorization for large-scale collaborative filtering
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Ranking with local regression and global alignment for cross media retrieval
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Latent dirichlet allocation for tag recommendation
Proceedings of the third ACM conference on Recommender systems
Can movies and books collaborate?: cross-domain collaborative filtering for sparsity reduction
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Knowledge Transfer among Heterogeneous Information Networks
ICDMW '09 Proceedings of the 2009 IEEE International Conference on Data Mining Workshops
IEEE Transactions on Knowledge and Data Engineering
Performance of recommender algorithms on top-n recommendation tasks
Proceedings of the fourth ACM conference on Recommender systems
A new approach to cross-modal multimedia retrieval
Proceedings of the international conference on Multimedia
Music recommendation by unified hypergraph: combining social media information and music content
Proceedings of the international conference on Multimedia
Collaborative topic modeling for recommending scientific articles
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Expectation-propagation for the generative aspect model
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Transfer learning to predict missing ratings via heterogeneous user feedbacks
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Cross-domain collaboration recommendation
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
| Hi-index | 0.01 |
Due to the scarcity of user interest information in the target domain, recommender systems generally suffer from the sparsity problem. To alleviate this limitation, one natural way is to transfer user interests in other domains to the target domain. However, objects in different domains may be in different media types, which make it very difficult to find the correlations between them. In this paper, we propose a Bayesian hierarchical approach based on Latent Dirichlet Allocation (LDA) to transfer user interests cross domains or media. We model documents (corresponding to media objects) from different domains and user interests in a common topic space, and learn topic distributions for documents and user interests together. Specifically, to learn the model, we combine multi-type media information: media descriptions, user-generated text data and ratings. With this model, recommendation can be done in multiple ways, via predicting ratings, comparing topic distributions of documents and user interests directly and so on. Experiments on two real world datasets demonstrate that our proposed method is effective in addressing the sparsity problem by transferring user interests cross domains.