Affiliations: [a] School of Marxism, Xidian University, Xi’an, Shaanxi, China
| [b] Business School, Sichuan University, Chengdu, Sichuan, China
| [c] School of Economics and Management, Xidian University, Xi’an, Shaanxi, China
Correspondence:
[*]
Corresponding authors. Y. Gao, School of Marxism, Xidian University, Xi’an, Shaanxi, China. E-mail: gaoyuxuan@xidian.edu.cn. and H. Liang, Business School, Sichuan University, Chengdu, Sichuan, China. E-mail: hmliang@xidian.edu.cn. and B. Sun, School of Economics and Management, Xidian University, Xi’an, Shaanxi, China. E-mail: bzsun@xidian.edu.cn.
Abstract: With the rapid development of e-commerce, whether network intelligent recommendation can attract customers has become a measure of customer retention on online shopping platforms. In the literature about network intelligent recommendation, there are few studies that consider the difference preference of customers in different time periods. This paper proposes the dynamic network intelligent hybrid recommendation algorithm distinguishing time periods (DIHR), it is a integrated novel model combined with the DEMATEL and TOPSIS method to solved the problem of network intelligent recommendation considering time periods. The proposed method makes use of the DEMATEL method for evaluating the preference relationship of customers for indexes of merchandises, and adopt the TOPSIS method combined with intuitionistic fuzzy number (IFN) for assessing and ranking the merchandises according to the indexes. We specifically introduce the calculation steps of the proposed method, and then calculate its application in the online shopping platform.
