Skip to main content

Naviz:Website Navigational Behavior Visualizer

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2336))

Abstract

Navigational behavior of website visitors can be extracted from web access log files with data mining techniques such as sequential pattern mining. Visualization of the discovered patterns is very helpful to understand how visitors navigate over the various pages on the site. Currently several web log visualization tools have been developed. However those tools are far from satisfactory. They do not provide global view of visitor access as well as individual traversal path effectively. Here we introduce Naviz, a system of interactive web log visualization that is designed to overcome those drawbacks. It combines two-dimensional graph of visitor access traversals that considers appropriate web traversal properties, i.e. hierarchization regarding traversal traffic and grouping of related pages, and facilities for filtering traversal paths by specifying visited pages and path attributes, such as number of hops, support and confidence. The tool also provides support for modern dynamic web pages. We apply the tool to visualize results of data mining study on web log data of Mobile Townpage, a directory service of phone numbers in Japan for i-Mode mobile internet users. The results indicate that our system can easily handle thousands of discovered patterns to discover interesting navigational behavior such as success paths, exit paths and lost paths.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. R. Srikant, and R. Agrawal. Mining Sequential Patterns: Generalizations and Performance Improvements. In Fifth Int’l Conference on Extending Database Technology (EDBT’96), pages 3–17, Avignon, France, March 1996.

    Google Scholar 

  2. Mukherjea, S & Foley, J., D. (1995). Visualizing the World-Wide Web with the Navigational View Builder. Computer Networks and ISDN Systems, 27(6), 1075–1087

    Article  Google Scholar 

  3. E. Gansner, E. Koutsofios, S. North, and K. Vo. A technique for drawing directed graphs. Transactions on Software Engineering, 19(3):214–230, March 1993.

    Google Scholar 

  4. Pitkow, J. and K. Bharat. WebViz: A Tool for World-Wide Web Access Log Analysis. In Proceedings of First International Conference on the World-Wide Web 1994.

    Google Scholar 

  5. M. Spiliopoulou and L.C. Faulstich. WUM: A Web Utilization Miner. EDBT Workshop WebDB98, Valencia, Spain, 1998. Springer Verlag.

    Google Scholar 

  6. Cugini, J. and J. Scholtz. VISVIP: 3D Visualization of Paths through Web Sites. In Proceedings of International Workshop on Web-Based Information Visualization (WebVis’99). Florence, Italy. pp. 259–263. IEEE Computer Society, September 1–3 1999.

    Google Scholar 

  7. Jason I. Hong, and James A. Landay, “WebQuilt: A Framework for Capturing and Visualizing the Web Experience.” In Proceedings of The Tenth International World Wide Web Conference (WWW10), Hong Kong, May 2001.

    Google Scholar 

  8. Kaidi Zhao, Bing Liu. “Visual Analysis of The Behavior of Discovered Rules.” To appear in Workshop Notes in ACM SIGKDD-2001 Workshop on Visual Data Mining, San Francisco, CA; Aug 20, 2001

    Google Scholar 

  9. http://www.research.att.com/sw/tools/graphviz/

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2002 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Prasetyo, B., Pramudiono, I., Takahashi, K., Kitsuregawa, M. (2002). Naviz:Website Navigational Behavior Visualizer. In: Chen, MS., Yu, P.S., Liu, B. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2002. Lecture Notes in Computer Science(), vol 2336. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47887-6_27

Download citation

  • DOI: https://doi.org/10.1007/3-540-47887-6_27

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43704-8

  • Online ISBN: 978-3-540-47887-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics