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AdMIRe 2011 : AdMIRe 2011- 3rd International Workshop on Advances in Music Information Research | |||||||||||||||
Link: http://www.cp.jku.at/conferences/AdMIRe2011/ | |||||||||||||||
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Call For Papers | |||||||||||||||
The 3rd International Workshop on Advances in Music Information Research (AdMIRe 2011) will serve as a forum for theoretical and practical discussions of cutting edge research in the fields of Web mining for music information extraction, retrieval, and recommendation as well as in mobile applications and services. Research on multimodal extraction, retrieval, and presentation with a focus on the music and audio domain is especially welcome, as well as submissions addressing concrete implementations of systems and services by both academic institutions and industrial companies. Music information retrieval (MIR) as a subfield of multimedia information retrieval has been a fast growing field of research during the past decade. In traditional MIR research, music-related information were extracted from the audio signal using signal processing techniques. These methods, however, cannot capture semantic information not encoded in the audio signal, but nonetheless essential to many consumers, e.g., the meaning of the lyrics of a song or the political motivation or background of a singer. In recent years, the emergence of various Web 2.0 platforms and services dedicated to the music and audio domain, like last.fm, MusicBrainz, or echonest, has provided novel and powerful, albeit noisy, sources for high level, semantic information on music artists, albums, songs, and others. The abundance of such information provided by the power of the crowd can therefore contribute to MIR research and development considerably. On the other hand, the wealth of newly available, semantically meaningful information offered on Web 2.0 platforms also poses new challenges, e.g., dealing with the huge amount and the noisiness of this kind of data, various user biases, hacking, or the cold start problem. Another recent trend, not at last addressable to platforms like Apple's iPhone or Google's Android, are intelligent user interfaces to access the large amounts of music usually available on today's mobile music players. Mobile devices that offer high speed Web access allow for even more music to be consumed via Web services. Dealing with these vast amounts of music requires intelligent services on mobile devices that provide, for example, personalized and context-aware music recommendations. The current emergence and confluence of these challenges make this an interesting field for researchers and industry practitioners alike. Call for Papers AdMIRe 2011 solicits regular technical papers of up to 6 pages following the ICME author guidelines. The proceedings of the workshop will be published as part of the IEEE ICME 2011 main conference proceedings and will be indexed by IEEE Xplore. Papers must be original and not submitted to or accepted by any other conference or journal. Moreover, we will seek opportunities to publish extended versions of particularly outstanding papers in a journal related to the field. All submissions to this workshop will be peer-reviewed by at least three Program Committee members. The review process will be double-blind. Topics of Interest Music Information Systems Multimodal User Interfaces Context-aware Music Applications User Modeling and Personalization Social Networks and Collaborative Tagging in the Music and Audio Domain Web Mining and Information Extraction in the Music Domain Combination of Web-based and Signal-based Information Extraction Methods Mining and Analysis of Music Video Clips Mining and Analysis of Music-Related Images / Artwork Music Recommendation Semantic Web, Linking Open Data and Open Web Services for the Music and Audio Domain Ontologies, Semantics and Reasoning in the Music and Audio Domain Similarity Measurement Evaluation, Mining of Ground Truth and Data Collections Music Information Retrieval, Services, and Applications for Mobile Devices Music Indexing and Retrieval Techniques Exploration and Discovery in Large Music Collections Multimodal Semantic Content Analysis |
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