An Approach for Sentiment Classification of Music

Francesco Colace, Luca Casaburi

Abstract

In recent years, the music recommendation systems and dynamic generation of playlists have become extremely promising research areas. Thanks to the widespread use of the Internet, users can store a consistent set of music data and use them in the everyday context thanks to portable music players. The problem of modern music recommendation systems is how to process this large amount of data and extract meaningful content descriptors. The aim of this paper is to compare different approaches to decode the content within the mood of a song and to propose a new set of features to be considered for classification.

References

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Paper Citation


in Harvard Style

Colace F. and Casaburi L. (2016). An Approach for Sentiment Classification of Music . In Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-187-8, pages 421-426. DOI: 10.5220/0005826504210426


in Bibtex Style

@conference{iceis16,
author={Francesco Colace and Luca Casaburi},
title={An Approach for Sentiment Classification of Music},
booktitle={Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2016},
pages={421-426},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005826504210426},
isbn={978-989-758-187-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - An Approach for Sentiment Classification of Music
SN - 978-989-758-187-8
AU - Colace F.
AU - Casaburi L.
PY - 2016
SP - 421
EP - 426
DO - 10.5220/0005826504210426