A collaborative filtering method for music recommendation using playing coefficients for artists and users
作者：
Highlights：
• Proposal of a collaborative filtering (CF) method for music recommendation.
• The method is based on user and artist characterization.
• Only playing information that can be implicitly obtained is needed.
• The proposal can be applied for both rating prediction and item recommendation.
• The method outperforms other CF approaches.
摘要
•Proposal of a collaborative filtering (CF) method for music recommendation.•The method is based on user and artist characterization.•Only playing information that can be implicitly obtained is needed.•The proposal can be applied for both rating prediction and item recommendation.•The method outperforms other CF approaches.
论文关键词：Collaborative filtering,Music recommendation,Data mining,Sparsity,Gray-sheep
论文评审过程：Received 22 June 2016, Revised 10 September 2016, Accepted 11 September 2016, Available online 13 September 2016, Version of Record 16 September 2016.
论文官网地址：https://doi.org/10.1016/j.eswa.2016.09.019
