loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Francesco Colace and Luca Casaburi

Affiliation: Università degli Studi di Salerno, Italy

Keyword(s): Sentiment Analysis, Recommender System, Knowledge Management.

Related Ontology Subjects/Areas/Topics: Collaborative and Social Interaction ; Emotional and Affective Computing ; Enterprise Information Systems ; Human-Computer Interaction ; Multimedia Systems

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.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.128.198.90

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
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; ISSN 2184-4992, SciTePress, pages 421-426. DOI: 10.5220/0005826504210426

@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},
issn={2184-4992},
}

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
IS - 2184-4992
AU - Colace, F.
AU - Casaburi, L.
PY - 2016
SP - 421
EP - 426
DO - 10.5220/0005826504210426
PB - SciTePress