Modeling behavior sequence for personalized fund recommendation with graphical deep collaborative filtering

作者：

Highlights：

• A personalized mutual fund recommender system is developed for precision marketing.

• The mutual funds are trained and represented by their periodic performance.

• The dynamic trading behaviors of customers are also modeled in this framework.

• The proposed graphical deep collaborative filtering can achieve high accuracy.

摘要

•A personalized mutual fund recommender system is developed for precision marketing.•The mutual funds are trained and represented by their periodic performance.•The dynamic trading behaviors of customers are also modeled in this framework.•The proposed graphical deep collaborative filtering can achieve high accuracy.

论文关键词：Deep collaborative filtering,Graph neural network,Node embedding,Mutual fund recommendation,Precision marketing

论文评审过程：Received 13 April 2021, Revised 22 November 2021, Accepted 25 November 2021, Available online 22 December 2021, Version of Record 3 January 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.116311