APPLICATION OF AN ANT COLONY ALGORITHM - For Song Categorising using Metadata

Nadia Lachetar, Halima Bahi

Abstract

Instead of the expansion of the information retrieval systems, the music information retrieval domain is still an open one. One of the promising areas in this context is the audio indexing databases. This paper addresses the problem of indexing database containing songs to enable their effective exploitation. Since, we are interested with songs databases, it is necessary to exploit the specific structure of the song in with each part plays a specific role. We propose to use the title and the artist particularities (in fact each artist tends to compose or sing a specific genre of music). In this article, we present our experiments in automated song categorisation, where we suggest the use of an ant colony algorithm. A naive Bayes algorithm is used as a baseline in our tests.

References

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Paper Citation


in Harvard Style

Lachetar N. and Bahi H. (2011). APPLICATION OF AN ANT COLONY ALGORITHM - For Song Categorising using Metadata . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2011) ISBN 978-989-8425-79-9, pages 371-376. DOI: 10.5220/0003631303790384


in Bibtex Style

@conference{kdir11,
author={Nadia Lachetar and Halima Bahi},
title={APPLICATION OF AN ANT COLONY ALGORITHM - For Song Categorising using Metadata},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2011)},
year={2011},
pages={371-376},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003631303790384},
isbn={978-989-8425-79-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2011)
TI - APPLICATION OF AN ANT COLONY ALGORITHM - For Song Categorising using Metadata
SN - 978-989-8425-79-9
AU - Lachetar N.
AU - Bahi H.
PY - 2011
SP - 371
EP - 376
DO - 10.5220/0003631303790384