VenueMusic: A venue-aware music recommender system

Zhiyong Cheng, Jialie Shen

Research output: Chapter in Book/Report/Conference proceedingConference Paper published in Proceedingspeer-review

Abstract

Users' music preferences can be greatly influenced by their location and environment nearby. In this demonstration, we present an intelligent music recommender system, called VenueMusic, to automatically identify suitable music for various popular venues in our daily lives. VenueMusic enjoys a set of nice features: i) music concept sequence generation scheme and Location-aware Topic Model (LTM) are proposed to map the characteristics of venues and music into a latent semantic space, where suitability of music for a venue can be directly measured, ii) a smart interface enabling user to smoothly interact with VenueMusic, and iii) high quality music playlist. The demonstration will show several interesting use-cases of VenueMusic, and illustrate its superiority on recommending music based on where user presents.

Original languageEnglish
Title of host publicationSIGIR 2015 - Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval
Place of PublicationSantiago; Chile
PublisherAssociation for Computing Machinery, Inc
Pages1029-1030
Number of pages2
ISBN (Electronic)9781450336215
DOIs
Publication statusPublished - 9 Aug 2015
Externally publishedYes
Event38th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2015 - Santiago, Chile
Duration: 9 Aug 201513 Aug 2015

Conference

Conference38th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2015
Country/TerritoryChile
CitySantiago
Period9/08/1513/08/15

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