Intelligent Mining Technology And Its Application Based On E-commerce

With the rapid development of internet technology,IT industry becomes the pillar of the new economic era,E-commerce has penetrated into every aspect of life.The valuable information how could be able to timely found in the massive information which generated in E-commerce and used to make scientific decisions,so that profits could be created has become the problem to be solved urgently for enterprises.Data mining can provide convenience for solving this problem.In this paper,customer value classification and sales of several important factors which affect the e-commerce have been chosen as the research object,and a lot of major work has been carried.On the one hand,for the classification of customer value,the paper described classification method based on support vector machine.Firstly,the paper studied on support vector machine classification method in theory,analyzed the great performance of support vector machine in solving non-linear,the curse of dimensionality and local minimum problems,and discussed the key factors influencing the performance of classification.Then,this paper incorporated the sales growth,the cost of services and trading volume in the competitive enterprise in customer value classification,applying SVM on customer classification of online e-commerce platform,and use different kernel functions and compared different parameters each other.On the other hand,neural network was used to forecast the sales.First,artificial neural network was used to forecast the sales which based on the historical sales.Then artificial neural network was used to forecast the sales which based on the historical sales of corresponding customer which according to the classification of customer value based on the theory of the support vector machine.First created BP neural network model,then obtained the predicting outcomes through initialize,train and simulate the network.The gray neural network model for forecasting sales has been established by using the result of the BP network,the final prediction results were analyzed and compared.In this paper,the classification of customer value based on the theory of the support vector machine has been achieved.By using the correlation of customer data and sales data,the gray neural network forecasting model has been established to predict the sales data.Based on this study,the theory of support vector machine(SVM)and the gray neural network has played a positive role in e-commerce activities,has provided reference data for customer management and marketing management,and has advantages in the study of small sample learning.