Exploring user-specific information in music retrieval

Zhiyong Cheng, Jialie Shen, Liqiang Nie, Tat Seng Chua, Mohan Kankanhalli

Research output: Chapter in Book/Report/Conference proceedingConference Paper published in Proceedings

Abstract

With the advancement of mobile computing technology and cloud-based streaming music service, user-centered music retrieval has become increasingly important. User-specific information has a fundamental impact on personal music preferences and interests. However, existing research pays little attention to the modeling and integration of user-specific information in music retrieval algorithms/models to facilitate music search. In this paper, we propose a novel model, named User-Information-Aware Music Interest Topic (UIAMIT) model. The model is able to effectively capture the influence of user-specific information on music preferences, and further associate users' music preferences and search terms under the same latent space. Based on this model, a user information aware retrieval system is developed, which can search and re-rank the results based on age-And/or gender-specific music preferences. A comprehensive experimental study demonstrates that our methods can significantly improve the search accuracy over existing text-based music retrieval methods.

Original languageEnglish
Title of host publicationSIGIR 2017 - Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval
Place of PublicationTokyo, Japan
PublisherAssociation for Computing Machinery, Inc
Pages655-664
Number of pages10
ISBN (Electronic)9781450350228
DOIs
Publication statusPublished - 7 Aug 2017
Externally publishedYes
Event40th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2017 - Tokyo, Shinjuku, Japan
Duration: 7 Aug 201711 Aug 2017

Conference

Conference40th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2017
CountryJapan
CityTokyo, Shinjuku
Period7/08/1711/08/17

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  • Cite this

    Cheng, Z., Shen, J., Nie, L., Chua, T. S., & Kankanhalli, M. (2017). Exploring user-specific information in music retrieval. In SIGIR 2017 - Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 655-664). Association for Computing Machinery, Inc. https://doi.org/10.1145/3077136.3080772