A Fuzzy Evaluation Algorithm of E-commerce Customers Based on Attributes Reduction

The evaluation algorithm is based on the attributes of data objects. There is a certain correlation between attributes, and attributes are divided into key attributes and secondary attributes. The evaluation from the data objects in a hierarchical design based on key attributes can reduce the data size and algorithm complexity, and without prejudice on the basis of evaluation results can improve the accuracy of the algorithm. This paper proposes an algorithm of attribute reduction based on rough set and the hierarchical evaluation based on fuzzy set. The algorithm of hierarchical fuzzy evaluation based on attributes reduction is described in detail by example. According to the analysis of the current evaluation of e-commerce customers, a superposition method based on fuzzy evaluation algorithm is presented. After Clustering analysis of customers, then the evaluation analysis will be processed on the clustered data. There are a lot of uncertain data of customer clustering, so the traditional method of classification and evaluation to the incomplete data will be very complex. Superposition evaluation algorithm based on fuzzy set can improve the reliability and accuracy of e-commerce customer evaluation. Evaluation of the e-commerce customer also can improve efficiency, service quality and profitability of e-commerce businesses.