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Titlebook: Music Recommendation and Discovery; The Long Tail, Long òscar Celma Book 2010 Springer-Verlag GmbH Berlin Heidelberg 2010 Filtering Algori

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發(fā)表于 2025-3-21 18:03:48 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Music Recommendation and Discovery
副標題The Long Tail, Long
編輯òscar Celma
視頻videohttp://file.papertrans.cn/642/641484/641484.mp4
概述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
圖書封面Titlebook: Music Recommendation and Discovery; The Long Tail, Long  òscar Celma Book 2010 Springer-Verlag GmbH Berlin Heidelberg 2010 Filtering Algori
描述In the last 15 years we have seen a major transformation in the world of music. - sicians use inexpensive personal computers instead of expensive recording studios to record, mix and engineer music. Musicians use the Internet to distribute their - sic for free instead of spending large amounts of money creating CDs, hiring trucks and shipping them to hundreds of record stores. As the cost to create and distribute recorded music has dropped, the amount of available music has grown dramatically. Twenty years ago a typical record store would have music by less than ten thousand artists, while today online music stores have music catalogs by nearly a million artists. While the amount of new music has grown, some of the traditional ways of ?nding music have diminished. Thirty years ago, the local radio DJ was a music tastemaker, ?nding new and interesting music for the local radio audience. Now - dio shows are programmed by large corporations that create playlists drawn from a limited pool of tracks. Similarly, record stores have been replaced by big box reta- ers that have ever-shrinking music departments. In the past, you could always ask the owner of the record store for music recomm
出版日期Book 2010
關鍵詞Filtering Algorithms; Music Information Retrieval; Recommender Systems; information retrieval; knowledge
版次1
doihttps://doi.org/10.1007/978-3-642-13287-2
isbn_softcover978-3-642-43953-7
isbn_ebook978-3-642-13287-2
copyrightSpringer-Verlag GmbH Berlin Heidelberg 2010
The information of publication is updating

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沙發(fā)
發(fā)表于 2025-3-21 22:15:33 | 只看該作者
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發(fā)表于 2025-3-22 04:07:04 | 只看該作者
https://doi.org/10.1007/978-3-642-13287-2Filtering Algorithms; Music Information Retrieval; Recommender Systems; information retrieval; knowledge
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發(fā)表于 2025-3-22 06:43:12 | 只看該作者
òscar CelmaStarts 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
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發(fā)表于 2025-3-22 10:31:02 | 只看該作者
Book 2010ow - dio shows are programmed by large corporations that create playlists drawn from a limited pool of tracks. Similarly, record stores have been replaced by big box reta- ers that have ever-shrinking music departments. In the past, you could always ask the owner of the record store for music recomm
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