Abstract: Sustainable development of the third-party payment platform is a very complex problem, the key of problem is the mining of potential customers in trading platform. This paper establishes the third-party payment rough complex networks, defines rough approximation degree, the probability principal value of complex networks and degree distribution, constructs a rough model of knowledge discovery, and gives a method based on rough set theory for knowledge discovery. The research on rough complex networks knowledge discovery method provides a quantitative and actionable method, which can solve the potential customers mining issues of the rough complex networks. This paper presents the concepts of rough complex networks, as well as degree distribution of the third-party payment rough   complex networks, which lay the theoretical foundation for the third-party payment issues. The research on knowledge discovery method adapts to the needs of dynamic knowledge system updates, so there is a broad application prospect.

Key words: the third-party payment, rough complex networks, time series analysis, knowledge discovery

摘要： 第三方支付平台的可持续发展是一个错综复杂的问题，解决问题的关键之一是平台潜在客户的挖掘。建立了第三方支付粗糙复杂网络，通过对该粗糙复杂网络的上下近似度、度分布和度的概率主值的研究，构建了第三方支付粗糙复杂网络知识发现模型，给出了基于粗糙集理论的时间序列分析法的求解方法。第三方支付粗糙复杂网络知识发现方法的研究，为第三方支付平台潜在客户的挖掘提供了定量化可操作的方法。提出了粗糙复杂网络的有关概念，以及第三方支付粗糙复杂网络的度分布，为第三方支付有关问题的研究奠定了理论基础；知识发现方法的研究，适应了动态知识系统更新的需求，因此有着广泛的应用前景。

关键词: 第三方支付, 粗糙复杂网络, 时间序列分析, 知识发现