Victor Perotti


At any given web site, 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 web site server logs makes understanding users a difficult, time consuming task. The present chapter explores the use of an adaptive neural identification of clusters of web pages that are frequently visited together by users. A web site 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 web site support the actual use of the site.

Publication Date



Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works in February 2014.

Document Type

Book Chapter

Department, Program, or Center

Accounting (SCB)


RIT – Main Campus