Abstract
We present a music recommendation system that incorporates both collaborative filtering and mood-based recommendations. The benefits of incorporating mood-based recommendations over both content/genre-based and collaborative filtering-based recommendation are illustrated by means of a real-world user evaluation in which 54 users took part in a one month long evaluation.
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.
References
Schafer, J.B., Konstan, J.A., Riedl, J.: E-Commerce Recommendation Applications. Data Mining and Knowledge Discovery 5, 115–153 (2001)
Herlocker, J.L., Konstan, J.A., Borchers, A., Riedl, J.: An algorithmic framework for performing collaborative filtering. In: ACM SIGIR 1999, Berkeley, CA, August 15-19 (1999)
Melville, P., Mooney, R.J., Nagarajan, R.: Content-Boosted Collaborative Filtering for Improved Recommendations. In: AAAI 2002, Palo Alto, CA, March 25-27 (2002)
Shardanand, U.: Social Information Filtering: Algorithms for Automating Word of Mouth. In: ACM CHI 1995, Denver, CO, May 7-11 (1995)
Lee, J.S., Lee, J.C.: Music for my Mood: A Music Recommendation System Based on Context Reasoning. In: Havinga, P., Lijding, M., Meratnia, N., Wegdam, M. (eds.) EuroSSC 2006. LNCS, vol. 4272, Springer, Heidelberg (2006)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mortensen, M., Gurrin, C., Johansen, D. (2008). Real-World Mood-Based Music Recommendation. In: Li, H., Liu, T., Ma, WY., Sakai, T., Wong, KF., Zhou, G. (eds) Information Retrieval Technology. AIRS 2008. Lecture Notes in Computer Science, vol 4993. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68636-1_57
Download citation
DOI: https://doi.org/10.1007/978-3-540-68636-1_57
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-68633-0
Online ISBN: 978-3-540-68636-1
eBook Packages: Computer ScienceComputer Science (R0)