Adaptive personalized recommender system using learning automata and items clustering

作者：

Highlights：

• Construct Adaptive user’s interest model using learning automata.

• Present heuristic formula for rating prediction based on the user interest.

• Create precise user profile to enhanced performance of recommendation system.

• Tracking change of user’s interest over time automatically that is research gap.

摘要

•Construct Adaptive user’s interest model using learning automata.•Present heuristic formula for rating prediction based on the user interest.•Create precise user profile to enhanced performance of recommendation system.•Tracking change of user’s interest over time automatically that is research gap.

论文关键词：Recommender system,Personalization,Adaptive user profile,Clustering,Learning automata

论文评审过程：Received 13 September 2021, Revised 16 December 2021, Accepted 19 December 2021, Available online 21 December 2021, Version of Record 22 January 2022.

论文官网地址：https://doi.org/10.1016/j.is.2021.101978