Web Mining for successful e-Business based on Artificial Intelligence Techniques

성공적인 e-Business를 위한 인공지능 기법 기반 웹 마이닝

  • 이장희 (한국기술교육대학교 산업경영학부) ;
  • 유성진 (한국과학기술원 산업공학과 지식기반시스템 연구실) ;
  • 박상찬 (한국과학기술원 산업공학과 지식기반시스템 연구실)
  • Published : 2002.12.01

Abstract

Web mining is an emerging science of applying modem data mining technologies to the problem of extracting valid, comprehensible, and actionable information from large databases of web in e-Business environment and of using it to make crucial e-Business decisions. In this paper, we present the noble framework of data visualization system based on web mining for analyzing the characteristics of on-line customers in e-Business. We also propose the framework of forecasting system for providing the forecasting information of sales/purchase through the use of web mining based on artificial intelligence techniques such as back-propagation network, memory-based reasoning, and self-organizing map.

웹 마이닝은 e-Business 환경하에서 존재하는 대량의 웹 데이터에 데이터 마이닝 기법을 적용하여 유용하고 이해 가능한 정보를 추출해내는 과정을 의미하는데, 성공적인 e-Business전개를 위한 핵심적인 기술이다. 본 논문은 인공지능 기법에 기반한 웹마이닝 기술을 활용하여 e-Business상의 온라인 고객의 특성을 분석할 수 있는 data visualization system과 구매 판매 예측시스템의 효과적인 구조와 핵심적인 분석절차를 제안하였다.

Keywords

References

  1. Interantional Journal of Man-Machine Studies v.36 Tolerating noisy,irrelevant and novel attributes in instance-based learning algorthms Aha, D.W.
  2. IEEE SMC'99 Conference Proceedings v.3 WISE;Business-to-Business E-Commerce Alonso, G.;Fiedler,U.;Hagen, C.;Lazcano, A.;Schuldt, H.;Weilerd, N.
  3. IEEE Transactions On Neural Networks v.8 Are Artificial Neural Networks Black Boxes? Bentiez, J.M.;Castro, J.L.;Requena, I.
  4. Submitted to the Future Generation Computer Systems special Issure on Data Mining Using Neural Networks for Data Mining Craven, M.W.;Shavlik, J.W.
  5. In Advance in Neural Information Proceeding(2) Optimal brain damage Cun, Y.L.;Denker, J.S.;Solla,S.A.;D.S. Touretzky(Ed.)
  6. European management journal v.19 no.6 Transfomative Power of e-Business Over Consumer Brands Dussart, C.
  7. IEEE Expert v.8 no.1 Applying Machine Learning to Seminconductor Manufacturing Irani, K.B.;Cheng, J.;Fayyad, U.M.;Quan, Z.
  8. Expert Systems With Applications v.15 Hybrid Machine Learning System For Integrated Yield Managament in Semicondutor Manufacturing Kang, B.S.;Lee, J.H.;Shin, C.K.;Yu, S.J.;Park, S.C.
  9. Biological Cybernetics v.43 Self-organized formation of topologically correct feature maps Kohonen, T.
  10. IEEE Transations On Knowledge and Data Enginnering v.8 Effective Data Mining Using Neural Networks Lu, H.;Setiono, R.
  11. IEEE Transations On Neural Networks v.4 Pruning Algorithms-A Survey Reed, R.
  12. Proceedings of International Joint Conference on Neural Networks v.Ⅱ Fault tolerance of pruned multilayer networks Segee, B.E.;Carter,M.J.
  13. IEEE Transations On Neural Networks v.8 Neural-Network Feature Selector Setiono, R.;Liu, H.
  14. Expert Systems With Applications v.16 Memory adn Neural Network Based Expert Systems Shin, C.K.;Park,S.C.
  15. Refining Sysbolic Knowledge Using Nerual Networks Machine Learninag;A Multistrategy Approach Towell, G.;Shavlik, W.
  16. IEEE IEMC '98 Forecasting in A Complex Environment Using Feature Manipulating Technique Added In Traditional Forecasting System Yu,S.J.;Lee, J.H.;Park, S.C.
  17. Working Paper Applying Machine Learning to the Analysis Of a Quality Survey in a Mobile Telecommunication Industry Yu,S.J.;Park, S.C.
  18. International Conferece on WECWIS Business-to-Business e-Commerce with Open Buying on the Internet Zhong, Tian;Liu, L.Y.;Jing, Li;Jen-Yao Chung