Three-way recommender systems based on random forests
作者：
Highlights：
•
• We propose a framework integrating three-way decision and random forests.
• We introduce a new recommender action to consult the user for the choice.
• We build a random forest to predict the probability that a user likes an item.
• The three-way thresholds are optimal for both the training set and the testing set.
摘要
•We propose a framework integrating three-way decision and random forests.•We introduce a new recommender action to consult the user for the choice.•We build a random forest to predict the probability that a user likes an item.•The three-way thresholds are optimal for both the training set and the testing set.
论文关键词：Cost sensitivity,Random forests,Recommender systems,Three-way decision
论文评审过程：Received 12 December 2014, Revised 26 March 2015, Accepted 25 June 2015, Available online 27 June 2015, Version of Record 3 December 2015.
论文官网地址：https://doi.org/10.1016/j.knosys.2015.06.019
