Advances in Clustering Collaborative Filtering by means of Fuzzy C-means and trust

作者：

Highlights：

• We propose two Clustering-based Collaborative Filtering (CF) algorithms.

• We design a model-based approach able to combine trust and similarity among users.

• Trust-aware CF increases the coverage of predictions without affecting the quality.

• Item-based Fuzzy C-means CF increases recommendation accuracy (real dataset).

摘要

•We propose two Clustering-based Collaborative Filtering (CF) algorithms.•We design a model-based approach able to combine trust and similarity among users.•Trust-aware CF increases the coverage of predictions without affecting the quality.•Item-based Fuzzy C-means CF increases recommendation accuracy (real dataset).

论文关键词：Recommendation system,Collaborative Filtering,Trust-aware recommendation system,Fuzzy Clustering,Web intelligence

论文评审过程：Available online 29 June 2013.

论文官网地址：https://doi.org/10.1016/j.eswa.2013.06.022