A knowledge discovery model for third-party payment networks based on rough set theory

Article type: Research Article

Authors: Cao, Lixia^{a; b; *} | Huang, Guangqiu^b | Chai, Weiwen^a

Affiliations: [a] College of Science, Xi’ an Technological University, Xi’an, Shaanxi, China | [b] School of Management, Xi’ an University of Architecture and Technology, Xi’an, Shannxi, China

Correspondence: [*] Corresponding author. Lixia Cao, No. 4, Jinhua North Road, Xi’an, China. Tel.: +86 13709118013; Fax: +86 029 86173025; E-mail: [email protected].

Abstract: The optimal development of third-party payment platforms presents some very complex problems. One of the key issues is to identify the most promising potential customers. Hence, customer mining has come to prominence in financial research. This paper describes a way of modeling a third-party payment system in the context of a rough complex network, underpinned by rough set theory. The study of knowledge discovery on rough complex networks provides a quantitative and actionable method, which can be used to mine potential customers in rough complex networks. In addition to developing a way of analyzing data on a third-party payment platform, the paper uncovers a new application area for rough set theory, pointing the way to further utilization of this technology.

Keywords: Third-party payment system, rough set theory, rough complex network

DOI: 10.3233/JIFS-161738

Journal: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 1, pp. 413-421, 2017