Just-for-Me: An adaptive personalization system for location-aware social music recommendation

Zhiyong Cheng, Jialie Shen, Tao Mei

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

Abstract

In recent years, location-aware music recommendation is increasing in popularity, as more and more users consume music on the move. In this demonstration, we present an intelligent system, called Just-for-Me, to facilitate accurate music recommendation based on where user presents. Our system is developed based on a novel probabilistic generative model, which can effectively integrate the location contexts and global music popularity trends. This approach allows us to gain more comprehensive modeling on user preference and thus significantly enhances the music recommendation performance.

Original languageEnglish
Title of host publicationSIGIR 2014 - Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval
Place of PublicationGold Coast,Australia
PublisherAssociation for Computing Machinery (ACM)
Pages1267-1268
Number of pages2
ISBN (Print)9781450322591
DOIs
Publication statusPublished - 6 Jul 2014
Externally publishedYes
Event37th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2014 - Gold Coast, QLD, Australia
Duration: 6 Jul 201411 Jul 2014

Conference

Conference37th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2014
CountryAustralia
CityGold Coast, QLD
Period6/07/1411/07/14

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    Cheng, Z., Shen, J., & Mei, T. (2014). Just-for-Me: An adaptive personalization system for location-aware social music recommendation. In SIGIR 2014 - Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 1267-1268). Association for Computing Machinery (ACM). https://doi.org/10.1145/2600428.2611187