Andreas Nürnberger, Sebastian Stober, Birger Larsen, Marcin's Adaptive Multimedia Retrieval: Semantics, Context, and PDF

By Andreas Nürnberger, Sebastian Stober, Birger Larsen, Marcin Detyniecki (eds.)

ISBN-10: 3319120921

ISBN-13: 9783319120928

ISBN-10: 331912093X

ISBN-13: 9783319120935

This e-book constitutes the completely refereed post-conference complaints of the tenth foreign convention on Adaptive Multimedia Retrieval, AMR 2012, held in Copenhagen, Denmark, in October 2012.

The 17 revised complete papers provided have been conscientiously reviewed and chosen from various submissions. The papers disguise themes of state-of-the-art contributions, positive factors and type, place context, language and semantics, tune retrieval, and adaption and HCI.

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Extra info for Adaptive Multimedia Retrieval: Semantics, Context, and Adaptation: 10th International Workshop, AMR 2012, Copenhagen, Denmark, October 24-25, 2012, Revised Selected Papers

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470]. , [471]. We are herein interested only in the ways systems for MGR are evaluated, be they algorithms, humans [79,169, 201,258,261,262,278,290,366,367,370,381,383,460], pigeons [347], sparrows [439, 440], koi [58], primates [278] or rats [317]. To facilitate this survey, we created a spreadsheet summarizing every relevant paper we found in terms of its experimental design, details of the datasets it uses, and the figures of merit it reports. This resource provides a simple means to delimit sets of references sharing particular aspects of evaluation.

221–224, Oct 2006 61. : Relevance feedback in an adaptive space with one-class SVM for content-based music retrieval. In: Proceedings of the ICALIP, pp. 1153–1158, July 2008 62. : Improving music genre classification using collaborative tagging data. In: International Conference on Web Search and Data Mining, Barcelona, Spain, Feb 2009 63. : Content-based music genre classification using timbral feature vectors and support vector machine. In: Proceedings of the International Conference on Interaction Sciences, pp.

638–642, July 2008 55. : Music genre classification via compressive sampling. In: Proceedings of the ISMIR, Amsterdam, The Netherlands, pp. 387–392, Aug 2010 56. : Performance evaluation of TreeQ and LVQ classifiers for music information retrieval. , et al. ) Artificial Intelligence and Innovations 2007: From Theory to Applications. IFIP, vol. 247, pp. 331–338. Springer, Boston (2007) 57. : GMM supervector for content based music similarity. L. Sturm 58. : Music discriminations by carp “Cyprinus carpio”.

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Adaptive Multimedia Retrieval: Semantics, Context, and Adaptation: 10th International Workshop, AMR 2012, Copenhagen, Denmark, October 24-25, 2012, Revised Selected Papers by Andreas Nürnberger, Sebastian Stober, Birger Larsen, Marcin Detyniecki (eds.)


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