earticle

논문검색

Customer Behavior Data Model using User Profile Analysis

초록

영어

Today, most of the companies have numerous issues to take advantage of the data within the organization. Modeling techniques could be described using profile and historical log data as a tool of data mining techniques. It is covered increasingly with data entry, research, processing, modeling and reporting components of the icon in the form of easy-to-use in many datamining tools. Visual data mining process can create a data stream. In this paper, customer behavior is predicted in pages or products, using the history profile analysis and the navigation items are necessary to predict unknown features.

목차

Abstract
 1. INTRODUCTION
 2. RELATED RESEARCH
  2.1 k-means clustering
  2.2 k-means clustering
 3. EXPERIMENTS
 4. Conclusions
 References

저자정보

  • Yong Gyu Jung Department of Medical IT Marketing, Eulji University, Korea
  • Agatha Lee Trulogic, Unit 4, 191 Parramatta Rd. Auburn NSW 2144 Australia
  • Jeong Chan Lee National DB Division, National Information Society Agency, Korea
  • Young Dae Lee International Promotion Agency of Culture Technology

참고문헌

자료제공 : 네이버학술정보

    함께 이용한 논문

      ※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

      0개의 논문이 장바구니에 담겼습니다.