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Study and Evaluation of user�s behavior in e-commerce Using Data Mining

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Author Affiliations

  • 1Department of Computer Science, SCMIPS, Indore, MP, INDIA

Res. J. Recent Sci., Volume 1, Issue (ISC-2011), Pages 375-387,(2012)

Abstract

Data mining has matured as a field of basic and applied research in computer science. The objective of this dissertation is to evaluate, propose and improve the use of some of the recent approaches, architectures and Web mining techniques (collecting personal information from customers) are the means of utilizing data mining methods to induce and extract useful information from Web information and service where data mining has been applied in the fields of e-commerce and e-business (that means User’s behavior). In the context of web mining, clustering could be used to cluster similar click-streams to determine learning behaviors in the case of e-learning or general site access behaviors in e-commerce. Most of the algorithms presented in the literature to deal with clustering web sessions treat sessions as sets of visited pages within a time period and do not consider the sequence of the click-stream visitation. This has a significant consequence when comparing similarities between web sessions. Wang and Zaiane propose an algorithm based on sequence alignment to measure similarities between web sessions where sessions are chronologically ordered sequences of page accesses.

References

  1. Shian-Hua Lin, Chi-Sheng Shih, Meng Chang Chen andet al., Extracting Classification Knowledge of InternetDocuments with Mining Term Associations: ASemantic Approach, In Proceedings of 21st AnnualInternational ACM SIGIR Conference on Research andDevelopment in Information Retrieval, Melbourne,Australia (1998)
  2. Cooley R., Mobasher B. and Srivsatava J., WebMining: Information and Pattern Discovery on theWord Wide Web, Technical Report TR 97-027,University of Minnesota, Dept. of Computer Science,Minneapolis, (1997)
  3. Bray T., Measuring the Web, In Proceedings of the 5thIntl. WWW Conference, Paris, France (1996)
  4. Chen M.S., Han J. and Yu P.S., Data Mining: AnOverview from a Database Perspective, IEEETransaction on Knowledge and Data Engineering, 8,866-833 (1996)
  5. Perkowitz M. and Etzioni O., Adaptive Web Sites:Conceptual Cluster Mining, In Proceeding of 16thInternational Joint Conference on Articial Intelligence,264-269, Stockholm, Sweden: Morgan Kaufmann,(1999)
  6. Mobasher B. and et al., Discovery and Evaluation ofAggregate Usage Profiles for Web Personalization, Data Mining and Knowledge Discovery (2002)
  7. Mobasher B., Web Usage Mining and Personalization,in Practical Handbook of Internet Computing, CRCPress, 15, 1-37 (2004)
  8. Ellen, Spertus and ParaSite, Mining StructuralInformation on the Web, In proceedings of 6thInternational WWW Conference, April, (1997)
  9. Wee-Keong Ng, Ee-Peng Lim, Chee-Thong Huang,Sourav Bhowmick, Fengqiong Qin, Web Warehousing:An Algebra for Web Information, In Proceedings of theIEEE Advances in Digital Libraries Conference, SantaBarbara, U.S.A., April, (1998)
  10. Wang K. and Liu H., Schema Discovery forSemistructured Data, In Proceedings of InternationalConference on Knowledge Discovery and Data Mining,Newport Beach, AAAI, Aug. (1997)
  11. Nestorov S., Abiteboul S. and Motwani R., InferringStructure in Semi structured Data, In Proceedings ofInternational Workshop on Management ofSemistructured Data, (1997)
  12. Zhou Y., Jin X. and Mobasher B., A RecommendationModel Based on Latent Principal Factors in WebNavigation Data, In Proceedings of the 3rdInternational Workshop on Web Dynamics, ACM Press,(2004)
  13. Bhowmick Sourav S., Madria S.K., Ng W.K. and LimE.P., Web Bags, Are They Useful in Web warehouse?In proceedings for 5th International Conference onFoundation of Data Organization, Japan, Nov. (1998)
  14. O’Malley M.J. and et al., Fuzzy Clustering of Childrenwith Cerebral Palsy Based on Temporal-Distance GaitParameters, IEEE Trans, ON Rehab. Eng., 5(4), 300-309 (1997)
  15. Han J. and Kamber M., Data Mining: Concepts andTechniques, (2007)
  16. Bhowmick Sourav S., Ng W.K. and Lim E.P., Information Coupling in Web Databases, InProceedings of the 17th International Conference onConceptual Modelling (ER’98), Singapore, November16-19, (1998)
  17. World Wide Web Consortium, Document Object Model(DOM) Level 1 Specification, http://www.w3.org/TR/,(1998)
  18. Wang K. and Liu H., Discovering Typical Structures ofDocuments: A Road Map Approach, ACM SIGR,August, (1998)
  19. Florescu D., Levy A. and Mendelzon A., DatabaseTechniques for the World Wide Web, A Survey,SIGMOD Record (1998)
  20. Inman V.T., Ralston H.J. and Todd F., HumanWalking, Baltimore (1981)
  21. H. Vernon Leighton and Srivastava J., Precision amongWWW Search Services (Search Engines): Alta Vista, Excite, Hotbot, Infoseek, Lycos (1997)
  22. Han J. and Fu Y., Discovery of Multi-level AssociationRules. In Proceedings of International Conference onVery Large Databases, pages 420-431, Zurich,Switzerland, Sept, (1995)
  23. Backman D. and Rubbin J., Web log analysis: Finding aRecipe for Success, (1997)
  24. Pitkow J., In Search of Reliable Usage Data on theWWW, In Proceedings of the 6th International WorldWide Web Conference, Santa Clara, California, April,(1997)
  25. Baeza-Yates R. and Ribeiro-Neto B., ModernInformation Retrieval, Addison Wesley, ACM Press(1999)
  26. O’Conner M. and Herlocker J., Clustering Items forCollaborative Filtering. In Proceedings of the ACMSIGIR Workshop on Recommender Systems, Berkeley,CA, USA: ACM Press (1999)
  27. Madria Anjay, Bhowmick Sourav S., Ng W.K. and LimE.P., Center for Advanced Information Systems, Schoolof Applied Science, Nanyang Technological University,Singapore 639798 {askumar, p517026, awkng,aseplim} ntu.edu.sg, undefined, undefined
  28. Petrovskiy Ikhail, Faculty of ComputationalMathematics and Cybernetics, Moscow StateUniversity Vorobjevy Gory, Moscow, Russiamichael cs.msu.su, undefined, undefined
  29. By Juan D. Velásquez, PhD University of Tokyo,Assistant Professor, Department of IndustrialEngineering University of Chile jvelasqu dii.uchile.clhttp://wi.dii.uchile.cl/, undefined, undefined
  30. Heikki Mannila Nokia Research Center, P.O. Box 407(Itamerenkatu 11) FIN-00045 Nokia Group, FinlandHeikki.Mannila nokia.com, undefined, undefined