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Music Recommendation and Discovery

The Long Tail, Long Fail, and Long Play in the Digital Music Space

Authors: Celma, Òscar

  • 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"
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eBook $54.99
price for USA
  • ISBN 978-3-642-13287-2
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Download immediately after purchase
Hardcover $69.99
price for USA
  • ISBN 978-3-642-13286-5
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $69.99
price for USA
  • ISBN 978-3-642-43953-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

With so much more music available these days, traditional ways of finding music have diminished. Today radio shows are often programmed by large corporations that create playlists drawn from a limited pool of tracks. Similarly, record stores have been replaced by big-box retailers that have ever-shrinking music departments. Instead of relying on DJs, record-store clerks or their friends for music recommendations, listeners are turning to machines to guide them to new music.

In this book, Òscar Celma guides us through the world of automatic music recommendation. He describes how music recommenders work, explores some of the limitations seen in current recommenders, offers techniques for evaluating the effectiveness of music recommendations and demonstrates how to build effective recommenders by offering two real-world recommender examples. He emphasizes the user's perceived quality, rather than the system's predictive accuracy when providing recommendations, thus allowing users to discover new music by exploiting the long tail of popularity and promoting novel and relevant material ("non-obvious recommendations"). In order to reach out into the long tail, he needs to weave techniques from complex network analysis and music information retrieval.

Aimed at final-year-undergraduate and graduate students working on recommender systems or music information retrieval, this book presents the state of the art of all the different techniques used to recommend items, focusing on the music domain as the underlying application.

Table of contents (9 chapters)

Buy this book

eBook $54.99
price for USA
  • ISBN 978-3-642-13287-2
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Download immediately after purchase
Hardcover $69.99
price for USA
  • ISBN 978-3-642-13286-5
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $69.99
price for USA
  • ISBN 978-3-642-43953-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Music Recommendation and Discovery
Book Subtitle
The Long Tail, Long Fail, and Long Play in the Digital Music Space
Authors
Copyright
2010
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag GmbH Berlin Heidelberg
eBook ISBN
978-3-642-13287-2
DOI
10.1007/978-3-642-13287-2
Hardcover ISBN
978-3-642-13286-5
Softcover ISBN
978-3-642-43953-7
Edition Number
1
Number of Pages
XVI, 194
Topics