Popular music retrieval by detecting mood
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Flickr tag recommendation based on collective knowledge
Proceedings of the 17th international conference on World Wide Web
Can all tags be used for search?
Proceedings of the 17th ACM conference on Information and knowledge management
How do you feel about "dancing queen"?: deriving mood & theme annotations from user tags
Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries
Web Semantics: Science, Services and Agents on the World Wide Web
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Music review classification enhanced by semantic information
APWeb'11 Proceedings of the 13th Asia-Pacific web conference on Web technologies and applications
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Music theme annotations would be really beneficial for supporting retrieval, but are often neglected by users while annotating. Thus, in order to support users in tagging and to fill the gaps in the tag space, in this paper we develop algorithms for recommending theme annotations. Our methods exploit already existing user tags, the lyrics of music tracks, as well as combinations of both. We compare the results for our recommended theme annotations against genre and style recommendations - a much easier and already studied task. We evaluate the quality of our recommended tags against an expert ground truth data set. Our results are promising and provide interesting insights into possible extensions for music tagging systems to support music search.