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Visualization and Analysis of Clickstream Data of Online Stores with a Parallel Coordinate System

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Electronic Commerce and Web Technologies (EC-Web 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1875))

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Abstract

Clickstreams are visitors’ path through a Web site. Analysis of clickstreams shows how a Web site is navigated and used by its visitors. Clickstream data of online stores contains information useful for understanding the effectiveness of marketing and merchandising efforts. In this paper, we present a visualization system that provides users with greater abilities to interpret and explore clickstream data of online stores. The system visualizes a large number of clickstreams by assigning parallel coordinates to sequential steps in clickstreams. To demonstrate how the presented visualization system provides capabilities for examining online store clickstreams, we present a series of parallel coordinate visualizations, which display clickstream data from an operating online retail store.

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References

  1. B. Berman and J. R. Evans, Retail Management: A Strategic Approach, 7th Edition, Prentice-Hall, Inc., 1998.

    Google Scholar 

  2. A. G. Büchner and M. Mulvenna, “Discovering Internet Marketing Intelligence through Online Analytical Web Usage Mining,” SIGMOD Record, 27(4):54–61, December 1998.

    Google Scholar 

  3. M. S. Chen, J. S. Park, P. S. Yu, “Data Mining for Traversal Patterns in a Web Environment,” Proc. of the 16th International Conference on Distributed Computing Systems, 1996.

    Google Scholar 

  4. E. Chi, J. Pitkow, J. Mackinlay, P. Pirolli, R. Gossweiler, and S. Card, “Visualizing the Evolution of Web Ecologies,” ACM CHI Conference on Human Factors in Computing Systems, 1998, pp. 400–407.

    Google Scholar 

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

    Google Scholar 

  6. H. Hochheiser, and B. Schneiderman, “Understanding Patterns of User Visits to Web Sites: Interactive Starfield Visualizations of WWW Log Data,” Technical Report, CS-TR-3989, Department of Computer Science, University of Maryland, 1999.

    Google Scholar 

  7. A. Inselberg and B. Dimsdale, “Parallel Coordinates A Tool for Visualizing Multivariate Relations,” Human-Machine Interactive Systems, Plenum Publishing Corporation, 1991, pp. 199–233.

    Google Scholar 

  8. J. Lee, M. Podlaseck, E. Schonberg and R. Hoch, “Visualization and Analysis of Clickstream Data of Online Stores for Understanding Web Merchandising,” To appear in the special issue of the International Journal of Data Mining and Knowledge Discovery on ECommerce and Data Mining, Kluwer Academic Publishers, 2000.

    Google Scholar 

  9. N. Papadakakis, E. P. Markatos, and A. E. Papathanasiou, “Palantir: a Visualization tool for the World Wide Web,” INET 98 Proceedings, 1998.

    Google Scholar 

  10. J. Pitkow, “In Search of Reliable Usage Data on the WWW,” Technical Report, College of Computing, Graphics, Visualization, and Usability Center, Georgia Tech, 1996.

    Google Scholar 

  11. L. Tauscher and S. Greenberg, “Revisitation Patterns in World Wide Web Navigation,” ACM CHI Conference on Human Factors in Computing Systems, 1997, pp. 399–406.

    Google Scholar 

  12. T. Wilson, “Web Site Mining Gets Granular,” InternetWeek, March 29, 1999.

    Google Scholar 

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© 2000 Springer-Verlag Berlin Heidelberg

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Lee, J., Podlaseck, M. (2000). Visualization and Analysis of Clickstream Data of Online Stores with a Parallel Coordinate System. In: Bauknecht, K., Madria, S.K., Pernul, G. (eds) Electronic Commerce and Web Technologies. EC-Web 2000. Lecture Notes in Computer Science, vol 1875. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44463-7_13

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  • DOI: https://doi.org/10.1007/3-540-44463-7_13

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67981-3

  • Online ISBN: 978-3-540-44463-3

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