The Journal of Machine Learning Research
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Usage patterns of collaborative tagging systems
Journal of Information Science
AutoTag: a collaborative approach to automated tag assignment for weblog posts
Proceedings of the 15th international conference on World Wide Web
The complex dynamics of collaborative tagging
Proceedings of the 16th international conference on World Wide Web
P-TAG: large scale automatic generation of personalized annotation tags for the web
Proceedings of the 16th international conference on World Wide Web
Combating web spam with trustrank
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Flickr tag recommendation based on collective knowledge
Proceedings of the 17th international conference on World Wide Web
Real-time automatic tag recommendation
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Tag Recommendations in Folksonomies
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
Tag recommendations based on tensor dimensionality reduction
Proceedings of the 2008 ACM conference on Recommender systems
Personalized, interactive tag recommendation for flickr
Proceedings of the 2008 ACM conference on Recommender systems
Can all tags be used for search?
Proceedings of the 17th ACM conference on Information and knowledge management
Efficient methods for topic model inference on streaming document collections
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
An Experimental Analysis of Suggestions in Collaborative Tagging
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Latent dirichlet allocation for tag recommendation
Proceedings of the third ACM conference on Recommender systems
Hierarchical Bayesian Models for Collaborative Tagging Systems
ICDM '09 Proceedings of the 2009 Ninth IEEE International Conference on Data Mining
I tag, you tag: translating tags for advanced user models
Proceedings of the third ACM international conference on Web search and data mining
Pairwise interaction tensor factorization for personalized tag recommendation
Proceedings of the third ACM international conference on Web search and data mining
The impact of resource title on tags in collaborative tagging systems
Proceedings of the 21st ACM conference on Hypertext and hypermedia
Automatic tag recommendation algorithms for social recommender systems
ACM Transactions on the Web (TWEB)
Information retrieval in folksonomies: search and ranking
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
Tripartite hidden topic models for personalised tag suggestion
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
Editorial: Special issue on advances in web intelligence
Neurocomputing
Semantic preference retrieval for querying knowledge bases
Proceedings of the 1st Joint International Workshop on Entity-Oriented and Semantic Search
Expert Systems with Applications: An International Journal
Recommending patents based on latent topics
Proceedings of the 7th ACM conference on Recommender systems
A collaborative filtering recommendation system combining semantics and Bayesian reasoning
AusDM '12 Proceedings of the Tenth Australasian Data Mining Conference - Volume 134
Flickr group recommendation based on user-generated tags and social relations via topic model
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part II
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More and more content on the Web is generated by users. To organize this information and make it accessible via current search technology, tagging systems have gained tremendous popularity. Especially for multimedia content they allow to annotate resources with keywords (tags) which opens the door for classic text-based information retrieval. To support the user in choosing the right keywords, tag recommendation algorithms have emerged. In this setting, not only the content is decisive for recommending relevant tags but also the user's preferences. In this paper we introduce an approach to personalized tag recommendation that combines a probabilistic model of tags from the resource with tags from the user. As models we investigate simple language models as well as Latent Dirichlet Allocation. Extensive experiments on a real world dataset crawled from a big tagging system show that personalization improves tag recommendation, and our approach significantly outperforms state-of-the-art approaches.