The complex dynamics of collaborative tagging
Proceedings of the 16th international conference on World Wide Web
Can all tags be used for search?
Proceedings of the 17th ACM conference on Information and knowledge management
Social tags: meaning and suggestions
Proceedings of the 17th ACM conference on Information and knowledge management
Learning to link with wikipedia
Proceedings of the 17th ACM conference on Information and knowledge management
Content-Based Clustering for Tag Cloud Visualization
ASONAM '09 Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining
A probabilistic model for personalized tag prediction
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
A generalized method for word sense disambiguation based on wikipedia
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
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The common tags given by multiple users to a particular document are often semantically relevant to the document and each tag represents a specific topic. In this paper, we attempt to emulate human tagging behavior to recommend tags by considering the concepts contained in documents. Specifically, we represent each document using a few most relevant concepts contained in the document, where the concept space is derived from Wikipedia. Tags are then recommended based on the tag concept model derived from the annotated documents of each tag. Evaluated on a Delicious dataset of more than 53K documents, the proposed technique achieved comparable tag recommendation accuracy as the state-of-the-art, while yielding an order of magnitude speed-up.