RecRisk: An enhanced recommendation model with multi-facet risk control

作者：

Highlights：

• Firstly consider two risky-facets in expert recommender systems.

• We design RecRisk incorporating heat equation and portfolio theory.

• First prove heat equation can be applied in expert and intelligent systems

• Efficiently evaluating the performance of RecRisk.

摘要

•Firstly consider two risky-facets in expert recommender systems.•We design RecRisk incorporating heat equation and portfolio theory.•First prove heat equation can be applied in expert and intelligent systems•Efficiently evaluating the performance of RecRisk.

论文关键词：Recommender systems,Trust,Heat equation,Portfolio theory

论文评审过程：Received 12 August 2019, Revised 3 April 2020, Accepted 11 May 2020, Available online 27 May 2020, Version of Record 20 June 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113561