Towards comprehensive profile aggregation methods for group recommendation based on the latent factor model
作者：
Highlights：
• We use latent factor matrices to enrich the profile aggregation.
• We aim at the profile aggregation with the contribution of all group members.
• The weight of each group member is determined in detail for each considered item.
• The neighbors are admitted to the group to clarify the interests of group members.
摘要
•We use latent factor matrices to enrich the profile aggregation.•We aim at the profile aggregation with the contribution of all group members.•The weight of each group member is determined in detail for each considered item.•The neighbors are admitted to the group to clarify the interests of group members.
论文关键词：Latent factor recommendation model,Profile aggregation,Group recommendation
论文评审过程：Received 13 April 2020, Revised 28 June 2021, Accepted 8 July 2021, Available online 14 July 2021, Version of Record 29 July 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.115585
