Classification of Cost and Quality of Product in E-Commerce Using Data Mining

Abstract

This paper discuss the development of an application for both consumers and companies, which would make use of information available on E-commerce websites to classify the data in accordance with the quality of the products available. Electronic commerce or E-commerce refers to the buying and selling of products over electronic systems such as the Internet. The amount of trade conducted electronically has grown extraordinarily with widespread Internet usage. In this paper we propose and analyze costs and relevant products in e-business fraud detection using different data mining techniques with help of ID3, J48, Naïve Bayes and Weka tool. Better presentation of accurate data by classifying all observations of fraud is presented. Keywords: E-Business, Fraud detection, Classification: ID3, J48 and Naive Bayes, Weka.