Ephemeral Context to Support Robust and Diverse Music Recommendations

While prior work on context-based music recommendation focused on fixed set of contexts (e.g. walking, driving, jogging), we propose to use multiple sensors and external data sources to describe momentary (ephemeral) context in a rich way with a very large number of possible states (e.g. jogging fas...

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Bibliographic Details
Published in:arXiv.org 2017-08
Main Authors: Kucherbaev, Pavel, Tintarev, Nava, Rodriguez, Carlos
Format: Article
Language:English
Subjects:
Context
Online Access:Get full text
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Summary:While prior work on context-based music recommendation focused on fixed set of contexts (e.g. walking, driving, jogging), we propose to use multiple sensors and external data sources to describe momentary (ephemeral) context in a rich way with a very large number of possible states (e.g. jogging fast along in downtown of Sydney under a heavy rain at night being tired and angry). With our approach, we address the problems which current approaches face: 1) a limited ability to infer context from missing or faulty sensor data; 2) an inability to use contextual information to support novel content discovery.
ISSN:2331-8422