TCFACO: Trust-aware collaborative filtering method based on ant colony optimization
作者：
Highlights：
• A social recommender system method called TCFACO is proposed.
• Trust statements are used as a side information to deal with the data sparsity and cold-start issues.
• TCFACO uses available rating values along with social trust relationships to rank users.
• TCFACO uses ACO to choose a set of valuable users with their associated weights.
• Final selected users are used in the rating prediction considering their similarities to the target user.
摘要
•A social recommender system method called TCFACO is proposed.•Trust statements are used as a side information to deal with the data sparsity and cold-start issues.•TCFACO uses available rating values along with social trust relationships to rank users.•TCFACO uses ACO to choose a set of valuable users with their associated weights.•Final selected users are used in the rating prediction considering their similarities to the target user.
论文关键词：Collaborative filtering,Recommender systems,Social trustinformation,Similarity measures,Ant colonyoptimization
论文评审过程：Received 27 June 2018, Revised 3 September 2018, Accepted 21 September 2018, Available online 22 September 2018, Version of Record 12 October 2018.
论文官网地址：https://doi.org/10.1016/j.eswa.2018.09.045
