Collaborative filtering via gaussian probabilistic latent semantic analysis
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
IEEE Transactions on Knowledge and Data Engineering
Text Classification without Negative Examples Revisit
IEEE Transactions on Knowledge and Data Engineering
Combining Subclassifiers in Text Categorization: A DST-Based Solution and a Case Study
IEEE Transactions on Knowledge and Data Engineering
Proceedings of the 2007 international ACM conference on Supporting group work
Tag-aware recommender systems by fusion of collaborative filtering algorithms
Proceedings of the 2008 ACM symposium on Applied computing
Improved recommendation based on collaborative tagging behaviors
Proceedings of the 13th international conference on Intelligent user interfaces
Factorization meets the neighborhood: a multifaceted collaborative filtering model
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Personalizing Navigation in Folksonomies Using Hierarchical Tag Clustering
DaWaK '08 Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery
Personalized recommendation in social tagging systems using hierarchical clustering
Proceedings of the 2008 ACM conference on Recommender systems
Tagsplanations: explaining recommendations using tags
Proceedings of the 14th international conference on Intelligent user interfaces
Learning to recognize valuable tags
Proceedings of the 14th international conference on Intelligent user interfaces
Tagommenders: connecting users to items through tags
Proceedings of the 18th international conference on World wide web
Transfer learning for collaborative filtering via a rating-matrix generative model
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
TagRec: Leveraging Tagging Wisdom for Recommendation
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 04
The impact of ambiguity and redundancy on tag recommendation in folksonomies
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
ICDM '09 Proceedings of the 2009 Ninth IEEE International Conference on Data Mining
Transfer metric learning by learning task relationships
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Using inferred tag ratings to improve user-based collaborative filtering
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Divergence measures based on the Shannon entropy
IEEE Transactions on Information Theory
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Exploiting social tag information has been a popular way to improve recommender systems in recent years. However, recommender systems could not be improved with tags when tags are sparse. We notice that, while the tags are sparse for recommendation on some target domains, related and relatively dense auxiliary tags may already exist in some other more mature application domains. This inspires us to transfer tags to improve recommender systems on cross domain. In this paper, we propose a Tag Transfer Learning (TTL) model for effective cross domain collaborative filtering. TTL has some novel features over traditional collaborative filtering on cross domain. TTL transfers tag topics, a kind of one-way knowledge, instead of user-item rating patterns which is two-way knowledge. TTL is based on the clustering approach but not matrix factorization. TTL also gives a quantitative analysis on "when to transfer". The experiment was conducted on the MovieLens data set. The experimental results reveal that our approach outperforms both the traditional user-based collaborative filtering and the tag-based recommenders.