Visualizing the World-Wide Web with the navigational view builder
Proceedings of the Third International World-Wide Web conference on Technology, tools and applications
WebQuilt: a framework for capturing and visualizing the web experience
Proceedings of the 10th international conference on World Wide Web
A Technique for Drawing Directed Graphs
IEEE Transactions on Software Engineering
Mining Sequential Patterns: Generalizations and Performance Improvements
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
VISVIP: 3D Visualization of Paths through Web Sites
DEXA '99 Proceedings of the 10th International Workshop on Database & Expert Systems Applications
Mining web navigations for intelligence
Decision Support Systems - Special issue: Intelligence and security informatics
Clustering of search engine keywords using access logs
DEXA'06 Proceedings of the 17th international conference on Database and Expert Systems Applications
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Navigational behavior of Website visitors can be extracted from web access log files with data mining techniques such a 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 visulization 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 effertively. Here we introduce Naviz, a system of interactive web log visulization 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 ptterns to discover interesting navigational behavior such as success paths, exit paths and lost paths.