A hybrid multi-criteria recommender system using ontology and neuro-fuzzy techniques

作者：

Highlights：

• A new semantic technique is presented to calculate the similarity between items.

• A new demographic similarity measure is applied between each pair of users.

• A convex combination of both user- and movie-based similarities is used.

• A Fuzzy-based weighting method is applied to achieve more accurate predictions.

• ANFIS is used to discover the relations between each criterion and the overall rating.

摘要

•A new semantic technique is presented to calculate the similarity between items.•A new demographic similarity measure is applied between each pair of users.•A convex combination of both user- and movie-based similarities is used.•A Fuzzy-based weighting method is applied to achieve more accurate predictions.•ANFIS is used to discover the relations between each criterion and the overall rating.

论文关键词：Recommender system,Multi-criteria,Collaborative filtering,Adaptive neuro-fuzzy inference system,Ontology,Semantic filtering

论文评审过程：Received 16 March 2016, Revised 31 December 2016, Accepted 31 December 2016, Available online 3 January 2017, Version of Record 9 January 2017.

论文官网地址：https://doi.org/10.1016/j.elerap.2016.12.005