Finding the Hidden Gems: Recommending Untagged Music
Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 2256-2260.
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.
@inproceedings{ijcai2011p376,
title = {Finding the Hidden Gems: Recommending Untagged Music},
author = {Horsburgh, Ben and Craw, Susan and Massie, Stewart and Boswell, Robin},
booktitle = {Proceedings of the Twenty-Second International Joint Conference on
Artificial Intelligence, {IJCAI-11}},
publisher = {AAAI Press/International Joint Conferences on Artificial Intelligence},
editor = {Toby Walsh},
pages = {2256--2260},
year = {2011},
month = {7},
doi = {10.5591/978-1-57735-516-8/IJCAI11-376},
url = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-376},
}
TY - CPAPER TI - Finding the Hidden Gems: Recommending Untagged Music AU - Horsburgh, Ben AU - Craw, Susan AU - Massie, Stewart AU - Boswell, Robin T2 - Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11 PB - AAAI Press/International Joint Conferences on Artificial Intelligence PY - 2011 SP - 2256 EP - 2260 DO - 10.5591/978-1-57735-516-8/IJCAI11-376 UR - https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-376 ER -Copied
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