Research on the Tendency of Consumer Online Shopping Based on Improved TOPSIS Method

• 作者: Donghuan Huang Pengfei Liu Yuekun Ma
• 来源期刊: 国际计算机前沿大会会议论文集
• 学科: 社会科学
• 关键词: PURCHASE TENDENCY ENTROPY Fuzzy TOPSIS Data MINING
• 年，卷（期）: 2015,（B12）
• 页码范围: 76-78
• 页数: 3页
• 分类号: C5

摘要

Analyzing and predicting the tendency of consumers online shopping is the precondition of providing personalized recommendation service,and has attracted more and more attentions.Most of e-commerce platform shave various types of products,and there exists tremendous difference in consumers’occupation,education background and other personalized features.This Paper realizes a TOPSIS Method which is based on entropy and fuzzy numbers.Compared to the traditional TOPSIS method,with the Association Rules mining method of data mining,the improved TOPSIS solves the problem in traditional TOPSIS method which requires manual intervention during execution.In this study,to implement intelligent tendency predicting and analysis of consumers online shopping based on data driven,three steps is carried out.Firstly,the data mining method is leveraged to obtain the fuzzy weights of evaluation indicator through analyzing the electric business transaction data,and then a fuzzy decision-making matrix is established between product and consumer’s attribute;finally,a product category sequence which can indicate the tendency of consumer online shopping is established through calculating.