Novel predictive model to improve the accuracy of collaborative filtering recommender systems
作者：
Highlights：
• We analyzed the shortages of the popular prediction method in collaborative filtering.
• A novel predictive model employs an optimization algorithm.
• We use GA, PSO, and DE to find the predictive model that suits the user context.
• We apply the new predictive model in collaborative filtering techniques.
• The predictive model show superior prediction accuracy.
摘要
•We analyzed the shortages of the popular prediction method in collaborative filtering.•A novel predictive model employs an optimization algorithm.•We use GA, PSO, and DE to find the predictive model that suits the user context.•We apply the new predictive model in collaborative filtering techniques.•The predictive model show superior prediction accuracy.
论文关键词：Recommender system,Collaborative filtering,Predictive model,Cold start,Sparsity,Semantic information,Genetic algorithms,Optimization
论文评审过程：Received 18 May 2020, Revised 21 September 2020, Accepted 19 October 2020, Available online 3 November 2020, Version of Record 12 November 2020.
论文官网地址：https://doi.org/10.1016/j.is.2020.101670
