科研成果详情

题名Learning listener's preference for music recommender system
作者
发表日期2015-10-20
会议名称2015 International Conference on Big Data Applications and Services, BigDAS 2015
会议录名称ACM International Conference Proceeding Series
ISBN9781450338462
卷号20-23-October-2015
页码229-232
会议日期October 20-23, 2015
会议地点Jeju Island
摘要

Along with the spread of digital music and recent growth in the digital music industry, the demands for music recommender are increasing. These days, listeners have increasingly preferred to digital real-time streamlining and downloading to listen to music because this is convenient and affordable for the listeners. In this paper, we propose music recommender system using learning listener's prefererece, such as Melon, Billboard, Bugs Music, Soribada, and Gini, with most popular current songs across all genres and styles. It is also necessary for us to make the task of calculating the preference with weight to reflect the preference of most popular current songs with its popular music charts on trends. We evaluated the proposed system on the data set of music sites to measure its performance. We reported some of the experimental result, which is better performance than the previous system. Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词Bayesian network(BN) Clustering Collaborative filtering(CF)
DOI10.1145/2837060.2837102
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语种英语English
Scopus入藏号2-s2.0-84996899170
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被引频次[WOS]:0   [WOS记录]     [WOS相关记录]
文献类型会议论文
条目标识符https://repository.uic.edu.cn/handle/39GCC9TT/6437
专题理工科技学院
通讯作者Moon, Song Chul
作者单位
1.Database and Bioinformatics Lab.,Chungbuk National University,Cheongju,South Korea
2.Dept. of Computer Science,Namseoul University,Cheonan-city,South Korea
3.Div. of Science and Technology,BNU-HKBU United International College,Zhuhai,China
推荐引用方式
GB/T 7714
Cho, Young Sung,Moon, Song Chul,Jeong, Seon Phil. Learning listener's preference for music recommender system[C], 2015: 229-232.
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