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Web Usage Mining through Associative Models

Paolo Giudici, Paola Cerchiello

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Abstract

The aim of this contribution is to show how the information, concerning the order in which the pages of a Web site are visited, can be profitably used to predict the visit behaviour at the site. Usually every click corresponds to the visualization of a Web page. Thus, a Web clickstream defines the sequence of the Web pages requested by a user. Such a sequence identifies a user session. Request access from your librarian to read this chapter's full text.

About this research paper

What this paper is about

The aim of this contribution is to show how the information, concerning the order in which the pages of a Web site are visited, can be profitably used to predict the visit behaviour at the site. Usually every click corresponds to the visualization of a Web page. Thus, a Web clickstream defines the sequence of the Web pages requested by a user. Such a sequence identifies a user session. Request access from your librarian to read this chapter's full text.

Why it matters

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Key contribution

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Method / approach

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Available abstract

The aim of this contribution is to show how the information, concerning the order in which the pages of a Web site are visited, can be profitably used to predict the visit behaviour at the site. Usually every click corresponds to the visualization of a Web page. Thus, a Web clickstream defines the sequence of the Web pages requested by a user. Such a sequence identifies a user session. Request access from your librarian to read this chapter's full text.

Key concepts: Clickstream, Computer science, Session (web analytics), World Wide Web, Web page, Web site, Static web page, Web navigation

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