An Application of Data Mining Technique in a Text-Image Shopping Engine

• Main Authors: Yi-Ting Lin, 林儀庭
• Other Authors: Hown-Wen Chen
• Format: Others
• Language: zh-TW
• Published: 2002
• Online Access: http://ndltd.ncl.edu.tw/handle/61437334998098790522

碩士 === 大葉大學 === 資訊管理研究所 === 90 === Internet is getting more and more popular and thus it becomes a way of people’s life. Users enjoy in getting much more information easily and in shopping comfortably through Internet. However, the amazing increasing amount of homepages causes difficulties in applying those information. In addition to the study of information retrieval, new techniques of data mining can improve the operation efficiency of web sites and become useful tools in providing customers more suitable services through computer networks. Especially, successful shopping web sites usually have strategies of operation based on the personal information of member, and their consuming preferences or trading patterns. This study introduces the techniques of Data Mining, such as clustering and association rules, into a text-image shopping engine. There are three kinds of data to analyze: personal data、searching patterns and combined both. Through the shopping engine, customers will find goods that are exactly what they want in a easy and fast way. Moreover, shopping web sites will learn shopping behaviors of consumers through the shopping engine in order to forming more proper marketing strategies.