An explicit trust and distrust clustering based collaborative filtering recommendation approach
作者：
Highlights：
• A SVD signs based trust and distrust clustering method is proposed.
• A trust inference method is proposed to compute indirect trust between users.
• A trust neighbors mining algorithm is proposed to discover trust users.
• A sparse rating complement algorithm is proposed to get dense user rating profiles.
• The TCCF method is efficient in terms of prediction accuracy and coverage.
摘要
•A SVD signs based trust and distrust clustering method is proposed.•A trust inference method is proposed to compute indirect trust between users.•A trust neighbors mining algorithm is proposed to discover trust users.•A sparse rating complement algorithm is proposed to get dense user rating profiles.•The TCCF method is efficient in terms of prediction accuracy and coverage.
论文关键词：Recommender systems,Trust clustering,Collaborative filtering,Data sparsity,Cold start
论文评审过程：Received 23 January 2017, Revised 11 June 2017, Accepted 27 June 2017, Available online 29 June 2017, Version of Record 17 August 2017.
论文官网地址：https://doi.org/10.1016/j.elerap.2017.06.005
