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A music recommendation method for large-scale music library on a heterogeneous platform

  • Beihang University
  • Aviation Institute

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Currently, music recommendation system is a research focus in music information retrieval and a typical system can handle millions of music in real time. However, online music libraries have exceeded ten-million magnitudes, such as Amazon MP3, which results in mismatching between music recommendation systems and music libraries. Thus, this paper presents a music recommendation method for retrieving the large-scale music library on a heterogeneous platform. Based on the music similarity algorithm, by combining the indexing mechanism with GPU hardware acceleration, we further enhance the processing scale of the proposed method. Experiments show that, without lowering the retrieval accuracy, the proposed music recommendation method has the ability to handle ten-million magnitude libraries online in a single server.

源语言英语
主期刊名Algorithms and Architectures for Parallel Processing - 14th International Conference, ICA3PP 2014, Proceedings
出版商Springer Verlag
472-482
页数11
版本PART 1
ISBN(印刷版)9783319111964
DOI
出版状态已出版 - 2014
活动14th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2014 - Dalian, 中国
期限: 24 8月 201427 8月 2014

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
编号PART 1
8630 LNCS
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议14th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2014
国家/地区中国
Dalian
时期24/08/1427/08/14

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