Music Recommendation and Discovery

书名：Music Recommendation and DiscoveryTheLongTail,LongFail,andLongPlayintheDigitalMusicSpace
作者：ÒscarCelma
译者：
ISBN：9783642132865
出版社：Springer
出版时间：2010-9-7
格式：epub/mobi/azw3/pdf
页数：194
豆瓣评分：

书籍简介：

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 Similarly, record stores have been replaced by big-box retailers that have ever-shrinking music departments.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.

作者简介：

书友短评：

@ Cheerz 第一本Kindlle book- – @ Cheerz 第一本Kindlle book- –

添加微信公众号:好书天下获取