Authors:
- Starts with a formalization of the general recommendation problem
- Presents the pros and cons of most-used recommendation approaches, with a focus on the music domain
- Combines elements from recommender systems, complex network analysis, music information retrieval, and personalization
- Emphasizes "user's perceived quality" versus "system's predictive accuracy"
- Includes supplementary material: sn.pub/extras
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Table of contents (9 chapters)
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Front Matter
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Back Matter
About this book
Authors and Affiliations
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BMAT, Barcelona, Spain
Òscar Celma
Bibliographic Information
Book Title: Music Recommendation and Discovery
Book Subtitle: The Long Tail, Long Fail, and Long Play in the Digital Music Space
Authors: Òscar Celma
DOI: https://doi.org/10.1007/978-3-642-13287-2
Publisher: Springer Berlin, Heidelberg
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag GmbH Berlin Heidelberg 2010
Hardcover ISBN: 978-3-642-13286-5Published: 05 September 2010
Softcover ISBN: 978-3-642-43953-7Published: 15 October 2014
eBook ISBN: 978-3-642-13287-2Published: 02 September 2010
Edition Number: 1
Number of Pages: XVI, 194
Topics: Information Storage and Retrieval, Discrete Mathematics in Computer Science, Artificial Intelligence, Music