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 language | English |
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Title of host publication | SIGIR 2017 - Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval |
Place of Publication | Tokyo, Japan |
Publisher | Association for Computing Machinery, Inc |
Pages | 655-664 |
Number of pages | 10 |
ISBN (Electronic) | 9781450350228 |
DOIs | |
Publication status | Published - 7 Aug 2017 |
Externally published | Yes |
Event | 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2017 - Tokyo, Shinjuku, Japan Duration: 7 Aug 2017 → 11 Aug 2017 |
Conference
Conference | 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2017 |
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Country/Territory | Japan |
City | Tokyo, Shinjuku |
Period | 7/08/17 → 11/08/17 |