Research on Financial Recommendation Algorithm Based on User Interest Evolution and Big Data

被引:1
作者
Shen, Qiuyang [1 ]
Shi, Yuliang [1 ]
Shao, Yong [1 ]
机构
[1] Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China
来源
2022 IEEE INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING, BIG DATA AND ALGORITHMS (EEBDA) | 2022年
关键词
Recommendation algorithm; Fund financing; Time series model; user interest evolution;
D O I
10.1109/EEBDA53927.2022.9744929
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This article aims to study the recommendation algorithm of financial wealth management products based on the Internet. Through the item information of fund wealth management products, it mainly includes wealth management products issued by banks and fund products issued by fund companies as well as user behavior information, combined with traditional collaborative filtering algorithms to obtain a recommendation list, and then add a time series model, consider the seven-day annual interest rate and other timesensitive attribute factors to improve the accuracy of the recommendation, and finally introduce the current more cutting-edge DIEN model algorithm to get the recommendation result, which integrates the sequence The model is used to simulate the change process of user interest over time, and the attention mechanism is introduced to improve the recommendation effect, thereby providing users with better product choices.
引用
收藏
页码:764 / 769
页数:6
相关论文
共 9 条
[1]  
Badrul Sarwar G. K. J. K., 2001, ITEM BASED COLLABORA
[2]  
Greg L., 2003, IEEE INTERNET COMPUT, V4
[3]  
Guorui Z., 2018, KDD 18 P 24 ACM SIGK
[4]  
Hao W., 2015, KDD 15 P 21 ACM SIGK
[5]  
M. O. S. S. Riku Togashi, 2021, WEB SEARCH DATA MINI
[6]  
Sandvig B. M. J. J., 2007, ROBUSTNESS COLLABORA
[7]  
Xiang Li C. W. J. T., 2020, ADVERSARIAL MULTIMOD
[8]   A Collaborative Filtering Recommendation Algorithm Based on User Confidence and Time Context [J].
Xu, Guangxia ;
Tang, Zhijing ;
Ma, Chuang ;
Liu, Yanbing ;
Daneshmand, Mahmoud .
JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING, 2019, 2019
[9]   Deep Interest Network for Click-Through Rate Prediction [J].
Zhou, Guorui ;
Zhu, Xiaoqiang ;
Song, Chengru ;
Fan, Ying ;
Zhu, Han ;
Ma, Xiao ;
Yan, Yanghui ;
Jin, Junqi ;
Li, Han ;
Gai, Kun .
KDD'18: PROCEEDINGS OF THE 24TH ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY & DATA MINING, 2018, :1059-1068