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A study on contextual influences on automatic playlist continuation

Author
Gkatzioura, A.; Sànchez-Marrè, M.; Jorge, A.
Type of activity
Journal article
Journal
Frontiers in artificial intelligence and applications
Date of publication
2018-10-01
Volume
308
First page
156
Last page
165
DOI
/www.doi.org/10.3233/978-1-61499-918-8-156
URL
http://ebooks.iospress.nl/publication/50403 Open in new window
Abstract
Recommender systems still mainly base their reasoning on pairwise interactions or information on individual entities, like item attributes or ratings, without properly evaluating the multiple dimensions of the recommendation problem. However, in many cases, like in music, items are rarely consumed in isolation, thus users rather need a set of items, selected to work well together, serving a specific purpose, while having some cognitive properties as a whole, related to their perception of qualit...
Keywords
automatic playlist continuation, case-based reasoning, contextual dimensions, hybrid recommender systems, latent topic models
Group of research
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center
KEMLG - Knowledge Engineering and Machine Learning Group

Participants