Ontology-Based Music Recommender System View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2015

AUTHORS

Miguel Ángel Rodríguez-García , Luis Omar Colombo-Mendoza , Rafael Valencia-García , Antonio A. Lopez-Lorca , Ghassan Beydoun

ABSTRACT

Recommender systems are modern applications that make suggestions to their users on a variety of items taking into account their preferences in many domains. These systems use people’s opinions to recommend to their end users items that are likely to be of their interest. They are designed to help users to decide on appropriate items and facilitate finding them in a very large collection of items. Traditional syntactic-based recommender systems suffer from several disadvantages, such as polysemy or synonymy, that limit its effectiveness. Semantic technologies provide a consistent and reliable basis for dealing with data at knowledge level. Adding semantically empowered techniques to recommender systems can significantly improve the overall quality of recom-mendations. In this work, a recommender system based on a Music ontology is presented. A preliminary evaluation of the system shows promising results. More... »

PAGES

39-46

Book

TITLE

Distributed Computing and Artificial Intelligence, 12th International Conference

ISBN

978-3-319-19637-4
978-3-319-19638-1

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-19638-1_5

DOI

http://dx.doi.org/10.1007/978-3-319-19638-1_5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1043227793


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