Publication Type

Conference Proceeding Article

Publication Date

4-2014

Abstract

The fast growth of online communities and increasing popularity of internet-accessing smart devices have significantly changed the way people consume and share music. As an emerging technology to facilitate effective music retrieval on the move, intelligent recommendation has been recently received great attentions in recent years. While a large amount of efforts have been invested in the field, the technology is still in its infancy. One of the major reasons for this stagnation is due to inability of the existing approaches to comprehensively take multiple kinds of contextual information into account. In the paper, we present a novel recommender system called Just-for-Me to facilitate effective social music recommendation by considering users’ location related contexts as well as global music popularity trends. We also develop an unified recommendation model to integrate the contextual factors as well as music contents simultaneously. Furthermore, pseudo-observations are proposed to overcome the cold-start and sparsity problems. An extensive experimental study based on different test collections demonstrates that Just-for-Me system can significantly improve the recommendation performance at various geo-locations.

Keywords

Music Information Retrieval, Location-Aware, Recommendation, Empirical Study

Discipline

Databases and Information Systems

Research Areas

Data Management and Analytics

Publication

ICMR Glasgow 2014: Proceedings of the ACM International Conference on Multimedia Retrieval 2014: April 1-4, 2014, Glasgow

First Page

185

Last Page

194

ISBN

9781450327824

Identifier

10.1145/2578726.2578751

Publisher

ACM

City or Country

New York

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://dx.doi.org/10.1145/2578726.2578751

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