Techniques for visualizing website usage patterns with an adaptive neural network

Authors:
Victor Perotti
Affiliations:
Rochester Institute of Technology College of Business
Venue:
Computing information technology
Year:
2003

Citing 3
Cited 0

Web usage mining for Web site evaluation

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Automatic personalization based on Web usage mining

Communications of the ACM
Self organization of a massive document collection

IEEE Transactions on Neural Networks

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Abstract

At any given Website, the flow of users' visitations represents a valuable source of information for Web professionals. However, the identification and interpretation of Web usage patterns is not necessarily an easy task. The sheer volume and complexity of the browsing patterns captured in the Website server logs makes understanding users a difficult, time-consuming task. The present chapter explores the use of an adaptive neural network to visualize the Website usage patterns. This visual representation supports the identification of clusters of Web pages that are frequently visited together by users. A Website designer can see, at a glance, the primary groups of Web pages that visitors browse. Further, the site structure can be readily compared to the usage clusters to measure how well the links at the Website support the actual use of the site.