Ben Horsburgh
Finding the hidden gems: recommending untagged music.
Horsburgh, Ben; Craw, Susan; Massie, Stewart; Boswell, Robin
Authors
Professor Susan Craw s.craw@rgu.ac.uk
Emeritus Professor
Dr Stewart Massie s.massie@rgu.ac.uk
Associate Professor
Robin Boswell
Abstract
We have developed a novel hybrid representation for Music Information Retrieval. Our representation is built by incorporating audio content into the tag space in a tag-track matrix, and then learning hybrid concepts using latent semantic analysis. We apply this representation to the task of music recommendation, using similarity-based retrieval from a query music track. We also develop a new approach to evaluating music recommender systems, which is based upon the relationship of users liking tracks. We are interested in measuring the recommendation quality, and the rate at which cold-start tracks are recommended. Our hybrid representation is able to outperform a tag-only representation, in terms of both recommendation quality and the rate that cold-start tracks are included as recommendations.
Citation
HORSBURGH, B., CRAW, S., MASSIE, S. and BOSWELL, R. 2011. Finding the hidden gems: recommending untagged music. In Proceedings of the 22nd International joint conference on artificial intelligence (IJCAI-11), 16-22 July 2011, Barcelona, Spain. Palo Alto: AAAI Press [online], pages 2256-2261. Available from: https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-376
Conference Name | 22nd International joint conference on artificial intelligence (IJCAI-11) |
---|---|
Conference Location | Barcelona, Spain |
Start Date | Jul 16, 2011 |
End Date | Jul 22, 2011 |
Acceptance Date | Mar 31, 2011 |
Online Publication Date | Dec 31, 2011 |
Publication Date | Dec 31, 2011 |
Deposit Date | Sep 18, 2013 |
Publicly Available Date | Sep 18, 2013 |
Publisher | Association for the Advancement of Artificial Intelligence |
Pages | 2256-2261 |
ISBN | 9781577355120 |
DOI | https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-376 |
Public URL | http://hdl.handle.net/10059/867 |
Files
HORSBURGH 2011 Finding the hidden gems
(345 Kb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by-nc-nd/4.0/
You might also like
CBR assisted context-aware surface realisation for data-to-text generation.
(2023)
Conference Proceeding
Content type profiling of data-to-text generation datasets.
(2022)
Conference Proceeding
A case-based approach for content planning in data-to-text generation.
(2022)
Conference Proceeding
A case-based approach to data-to-text generation.
(2021)
Conference Proceeding