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For an up-to-date list of publications from the Music Technology Group see the
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Music Retrieval based on a Multi-Samples Selection Strategy for Support Vector Machine Active Learning
| Title | Music Retrieval based on a Multi-Samples Selection Strategy for Support Vector Machine Active Learning |
| Publication Type | Conference Paper |
| Year of Publication | 2009 |
| Conference Name | 24th Annual ACM Symposium on Applied Computing |
| Authors | Wang, T. - G. , Chen G. , & Herrera P. |
| Conference Start Date | 09/03/2009 |
| Conference Location | Honolulu, Hawaii, USA |
| Abstract | In active learning based music retrieval systems, providing multiple samples to the user for feedback is very necessary. In this paper, we present a new multi-samples selection strategy designed for support vector machine active learning. Aiming to reduce the redundancy between the selected samples, the strategy enforces the selected samples to be diverse by explicitly maximizing the distance between each other in the feature space. Experimental results on a music genre database demonstrated the effectiveness of the proposed strategy in selecting relevant multiple samples for human feedback on them. |
| preprint/postprint document | http://mtg.upf.edu/files/publications/Wang-ACM-2008.pdf |
