The Application of Neural Network Technology in Electronic Commerce Evaluation System

Abstract

Customer relationship management data mining are introduced In this paper. BP neural network is used in intelligent business-to-customer relationship evaluation. The customer relationship evaluation model is built based on the evaluation index system, which can train data samples and then obtain evaluation results. This paper also describes analysis of a customer relationship evaluation system based on neural network technology that is implemented using ASP.NET 2.0, SQL Server 2005 and MATLAB, conceptual design of the system, and implementation of the system. It is worth mentioning that the system has solved the MATLAB mixed programming problem, which promote the programming development of MATLAB application. With the increasing popularity of e-commerce technology, customer relationship management (CRM) is increasingly becoming the wide attention and research focus in business community and academic world. Customers have become one of the most important and valuable intangible assets in a modern enterprise. Customer retention is an important issue in the research and practice of customer relationship management (1). In order to achieve customer retention effectively, the accurate customer relationship evaluation is especially important, which will help the enterprises carry out better targeted customer marketing decision-making management. Evaluating customer relationship effectively is the prerequisite and guarantee to customer relationship management goals. Evaluation methods like K- means, fuzzy analytic hierarchy process were used before. But the complexity of customer relationship evaluation being affected by various factors shows non-linear characteristics, which makes it difficult to meet evaluation requirements fully using general mathematical methods. Fuzzy analytic hierarchy process can solve the problem about the weight of evaluation index system, but human subjective factors and decisions affected the evaluation and customer relationship data stored in the databases with information technologies being widely used in enterprises can not be leveraged effectively. The data mining technology can effectively deal with the problem of obtaining useful information from the vast amounts of information. The information-processing capacity of non-linear and adaptive features of BP neural network in data mining technologies overcome the shortcomings of traditional methods to better simulate a variety of factors influencing on the evaluation complexly, which is advantage and feasible. This paper aims at customer relationship evaluation based on BP neural network, and develops an e-commerce customer relationship evaluation system based on Web. MATLAB neural network toolbox components are also embedded in the system. The customer relationship in a restaurant as a case is studied to implement a valid evaluation of customer relationship.