2002 | OriginalPaper | Buchkapitel
Naviz:Website Navigational Behavior Visualizer
verfasst von : Bowo Prasetyo, Iko Pramudiono, Katsumi Takahashi, Masaru Kitsuregawa
Erschienen in: Advances in Knowledge Discovery and Data Mining
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
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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.