Name
Title | ||
|---|---|---|
A knowledge discovery model for third-party payment networks based on rough set theory. |
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. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.3233/JIFS-161738 | JOURNAL OF INTELLIGENT & FUZZY SYSTEMS |
Keywords | Field | DocType |
Third-party payment system,rough set theory,rough complex network | Data science,Rough set,Third party,Knowledge extraction,Payment,Mathematics | Journal |
Volume | Issue | ISSN |
33 | 1 | 1064-1246 |
Citations | PageRank | References |
0 | 0.34 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lixia Cao | 1 | 0 | 0.68 |
| Guangqiu Huang | 2 | 0 | 1.01 |
| Weiwen Chai | 3 | 0 | 0.34 |