Abstract
In this paper, we propose Context-based Music Recommendation (COMUS) ontology for modeling user’s musical preferences and context for supporting reasoning about the user’s desired emotion and preferences. The COMUS provides an upper Music Ontology that captures concepts about the general properties of music such as title, artists and genre and also provides extensibility for adding domain-specific ontologies, such as Music Feature, Mood and Situation, in a hierarchical manner. The COMUS is music dedicated ontology in OWL constructed by incorporating domain specific classes for music recommendation into the Music Ontology. Using this context ontology, we believe that the use of logical reasoning rules by checking the consistency of context information, and reasoning over the high-level, implicit context from the low-level, explicit information. As a novelty, our ontology can express detailed and complicated relations among the music, moods and situations, enabling users to find appropriate music for the application. We present some of the experiments we performed as a case-study for music recommendation.
This research was supported by the ubiquitous Computing and Network (UCN) Project, the Ministry of Knowledge and Economy (MKE) 21st Century Frontier R&D Program in Korea.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Birmingham, W., Dannenberg, R., Pardo, B.: An Introduction to Query by Humming with the VocalSearch System. Communications of the ACM 49(8), 49–52 (2006)
Rho, S., Han, B., Hwang, E., Kim, M.: MUSEMBLE: A Novel Music Retrieval System with Automatic Voice Query Transcription and Reformulation. Journal of Systems and Software 81(7), 1065–1080 (2008)
Oscar, C.: Foafing the Music: Bridging the semantic gap in music recommendation. In: Proceedings of 5th International Semantic Web Conference (ISWC) (2006)
Oscar, C., Perfecto, H., Xavier, S.: A multimodal approach to bridge the Music Semantic Gap. In: Semantic and Digital Media Technologies (SAMT) (2006)
Yves, R., Frederick, G.: Music Ontology Specification, http://www.musicontology.com/
Yves, R., Samer, A., Mark, S., Frederick, G.: The Music Ontology. In: Proceedings of the International Conference on Music Information Retrieval, ISMIR 2007, pp. 417–422 (2007)
Kanzaki Music Vocabulary, http://www.kanzaki.com/ns/music
MusicBrainz, http://musicbrainz.org
Protégé (ed.), http://protege.stanford.edu
Grüninger, M., Fox, M.S.: The Role of Mariano Fernández López 4-12 Competency Questions in Enterprise Engineering. In: IFIP WG 5.7 Workshop on Benchmarking. Theory and Practice, Trondheim, Norway (1994)
All Music Guide, http://allmusic.com
W3C. RDF Specification, http://www.w3c.org/RDF
Francois, P., Daniel, C.: A Taxonomy of Musical Genres. In: Content-Based Multimedia Information Access Conference (RIAO) (2000)
Samer, A., Yves, R., Mark, S.: An ontology-based approach to information management for music analysis systems. In: Proceedings of the 120th AES convention (2006)
Klaus, R.S., Marcel, R.Z.: Emotional Effects of Music: Production Rules. In: Music and emotion: theory and research. Oxford University Press, Oxford (2001)
Song, S., Rho, S., Hwang, E., Kim, M.: Music Ontology for Mood and Situation Reasoning to Support Music Retrieval and Recommendation. In: ICDS 2009 (to appear, 2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rho, S., Song, S., Hwang, E., Kim, M. (2009). COMUS: Ontological and Rule-Based Reasoning for Music Recommendation System. In: Theeramunkong, T., Kijsirikul, B., Cercone, N., Ho, TB. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2009. Lecture Notes in Computer Science(), vol 5476. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01307-2_89
Download citation
DOI: https://doi.org/10.1007/978-3-642-01307-2_89
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01306-5
Online ISBN: 978-3-642-01307-2
eBook Packages: Computer ScienceComputer Science (R0)