A recommender model based on strong and weak social Ties: A Long-tail distribution perspective

作者：

Highlights：

• A collaborative filtering recommender model for E-commerce users is proposed.

• Strong and weak social ties and long-tail distribution items are considered.

• Incentive coefficients for long-tail items based on triadic closure regulation are used.

• Diversity and novelty are enhanced and levels of accuracy maintains acceptable.

摘要

•A collaborative filtering recommender model for E-commerce users is proposed.•Strong and weak social ties and long-tail distribution items are considered.•Incentive coefficients for long-tail items based on triadic closure regulation are used.•Diversity and novelty are enhanced and levels of accuracy maintains acceptable.

论文关键词：Recommender systems,Social ties,PageRank algorithm,Long-tail distributions

论文评审过程：Received 21 June 2020, Revised 3 February 2021, Accepted 24 June 2021, Available online 29 June 2021, Version of Record 1 July 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115483