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On the Deployment of Web Usage Mining

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3209))

Abstract

In this paper we look at the deployment of web usage mining results within two key application areas of web measurement and knowledge generation for personalisation. We take a fresh look at the model of interaction between business and visitors to their web sites and the sources of data generated during these interactions. We then look at previous attempts at measuring the effectiveness of the web as a channel to customers and describe our approach, based on scenario development and measurement to gain insights into customer behaviour. We then present Concerto, a platform for deploying knowledge on customer behaviour with the aim of providing a more personalized service. We also look at approaches to measuring the effectiveness of the personalization. Various standards that are emerging in the market that can ease the integration effort of personalization and similar knowledge deployment engines within the existing IT infrastructure of an organization are also presented. Finally, current challenges in the deployment of web usage mining are presented.

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References

  1. Alpert, S., Karat, J., Karat, C.-M., Brodie, C., Vergo, J.: User attitudes regarding a useradaptive e-commerce Web Site. User Modeling and User-Adapted Interaction 13, 373–396 (2003)

    Article  Google Scholar 

  2. Berthon, P., Pitt, L.: Watson Richard. The world wide web as advertising medium: toward an understanding of conversion efficiency. The Journal of Advertising Research 36(1), 43–54

    Google Scholar 

  3. Büchner, A.G., Baumgarten, M., Anand, S.S., Mulvenna, M.D., Hughes, J.G.: Navigation Pattern Discovery from Internet Data. In: Masand, B., Spiliopoulou, M. (eds.) Advances in Web Usage Analysis and User Profiling. Lecturer Notes in Computer Science, Springer, Heidelberg (2000)

    Google Scholar 

  4. Burke, R.: Hybrid Recommender Systems: Survey and Experiments, To appear in User Modeling and User-Adapted Interaction

    Google Scholar 

  5. Cooley, R., Tan, P.-N., Srivastava, J.: Discovery of Interesting Usage Patter s from Web Data, Web Usage Analysis and User Profiling. In: Masand, B., Spiliopoulou, M. (eds.). LNCS (LNAI), pp. 163–182 (2000)

    Google Scholar 

  6. Joshi, A., Joshi, K., Krishnapuram, R.: On mining Web Access Logs. In: Proceedings of the ACM-SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, pp. 63–69 (2000)

    Google Scholar 

  7. Karat, C.-M., Brodie, C., Karat, J., Vergo, J., Alpert, S.: Personalizing the user experience on ibm.com. IBM Systems Journal 42(4) (2003)

    Google Scholar 

  8. Kim, J.K., Cho, Y.H., Kim, W.J., Kim, J.R., Suh, J.H.: A Personalized Recommendation Procedure for Internet Shopping Support. Electronic Commerce Research and Applications 1(3-4), 301–313 (2002)

    Article  Google Scholar 

  9. Lee, J., Podlaseck, M., Schonberg, E., Hoch, R., Gomory, S.: Analysis and Visualization of Metrics for Online Merchandising. In: Masand, B., Spiliopoulou, M. (eds.) WebKDD 1999. LNCS (LNAI), vol. 1836, pp. 126–141. Springer, Heidelberg (2000) ISSN: 0302-9743

    Chapter  Google Scholar 

  10. Mobasher, B., Cooley, R., Srivastava, J.: Data Preparation for Mining World Wide Web Browsing Patterns. The Journal of Knowledge and Information Systems 1(1) (1999)

    Google Scholar 

  11. Mobasher, B., Dai, H., Luo, T., Sung, Y., Nakagawa, M., Wiltshire, J.: Discovery of Aggregate Usage Profiles for Web Personalization. In: Proceedings of the Web Mining for E-Commerce Workshop (WebKDD 2000), held in conjunction with the ACM-SIGKDD Conference on Knowledge Discovery in Databases (KDD 2000), Boston (August 2000)

    Google Scholar 

  12. Mobasher, B., Dai, H., Luo, T., Nakagawa, M.: Using Sequential and Non-Sequential Patterns for Predictive Web Usage Mining Tasks. In: Proceedings of the IEEE International Conference on Data Mining (ICDM 2002), Maebashi City, Japan (December 2002)

    Google Scholar 

  13. Nakagawa, M., Mobasher, B.: Impact of Site Characteristics on Recommendation Models Based On Association Rules and Sequential Patterns. In: Proceedings of the IJCAI 2003 Workshop on Intelligent Techniques for Web Personalization, Acapulco, Mexico (August 2003)

    Google Scholar 

  14. Perkowitz, M., Etzioni, O.: Towards adaptive Web sites: Conceptual framework and case study. Artificial Intelligence 118, 245–275 (2000)

    Article  MATH  Google Scholar 

  15. Peyton, L.: Measuring and Managing the Effectiveness of Personalization. In: Proceedings of the 5th International conference on Electronic commerce, Pittsburgh, Pennsylvania (2003)

    Google Scholar 

  16. Resnick, P., Varian, H.R.: Recommender Systems. Communications of the ACM 40(3), 56–58 (1997)

    Article  Google Scholar 

  17. Schafer, J.B., Konstan, J., Riedl, J.: ‘Recommender Systems in E-Commerce’. In: EC 1999: Proceedings of the First ACM Conference on Electronic Commerce, Denver, CO, pp. 158–166 (1999)

    Google Scholar 

  18. Spiliopoulou, M., Pohle, C.: Data Mining for Measuring and Improving the Success of Web Sites. Data Mining and Knowledge Discovery 5, 85–114 (2001)

    Article  MATH  Google Scholar 

  19. Teltzrow, M., Berendt, B.: Web-Usage-Based Success Metrics for Multi-Channel Businesses. In: Proceedings of the Fifth WEBKDD workshop: Webmining as a Premise to Effective and Intelligent Web Applications (WEBKDD 2003), Washington, DC, USA, August 27 (2003)

    Google Scholar 

  20. Terveen, L., Hill, W.: Human-Computer Collaboration in Recommender Systems. In: Carroll, J. (ed.) Human Computer Interaction in the New Millennium, Addison-Wesley, New York (2001)

    Google Scholar 

  21. Yang, Y., Padmanabhan, B.: On Evaluating Online Personalization. In: Proceedings of the Workshop on Information Technology and Systems (WITS 2001), pp. 35–41 (December 2001)

    Google Scholar 

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© 2004 Springer-Verlag Berlin Heidelberg

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Anand, S.S., Mulvenna, M., Chevalier, K. (2004). On the Deployment of Web Usage Mining. In: Berendt, B., Hotho, A., Mladenič, D., van Someren, M., Spiliopoulou, M., Stumme, G. (eds) Web Mining: From Web to Semantic Web. EWMF 2003. Lecture Notes in Computer Science(), vol 3209. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30123-3_2

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  • DOI: https://doi.org/10.1007/978-3-540-30123-3_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23258-2

  • Online ISBN: 978-3-540-30123-3

  • eBook Packages: Springer Book Archive

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