2009•International Journal of Web Engineering and TechnologyRequires access

Identifying web navigation behaviour and patterns automatically from clickstream data

I‐Hsien Ting, Lillian M. Clark, Chris Kimble

Open publisher page 13 citations

Abstract

A user's clickstream, such as that which is found in server-side logs, can be a rich source of data concerning the ways in which a user navigates a site, but the volume and level of detail found in these logs makes it difficult to identify and categorise specific navigational patterns. In this paper, we describe the three-step automatic pattern discovery (APD) method, a tool that utilises sequential mining to extract a user's navigation route based on two levels of basic navigational elements. This paper contains descriptions of two studies in which the APD was used; the first makes use of APD to analyse the usage of an educational website; the second describes how APD was used to improve the design of a technical support website in a university department.

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What this paper is about

A user's clickstream, such as that which is found in server-side logs, can be a rich source of data concerning the ways in which a user navigates a site, but the volume and level of detail found in these logs makes it difficult to identify and categorise specific navigational patterns. In this paper, we describe the three-step automatic pattern discovery (APD) method, a tool that utilises sequential mining to extract a user's navigation route based on two levels of basic navigational elements. This paper contains descriptions of two studies in which the APD was used; the first makes use of APD to analyse the usage of an educational website; the second describes how APD was used to improve the design of a technical support website in a university department.

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Available abstract

A user's clickstream, such as that which is found in server-side logs, can be a rich source of data concerning the ways in which a user navigates a site, but the volume and level of detail found in these logs makes it difficult to identify and categorise specific navigational patterns. In this paper, we describe the three-step automatic pattern discovery (APD) method, a tool that utilises sequential mining to extract a user's navigation route based on two levels of basic navigational elements. This paper contains descriptions of two studies in which the APD was used; the first makes use of APD to analyse the usage of an educational website; the second describes how APD was used to improve the design of a technical support website in a university department.

Key concepts: Clickstream, Computer science, World Wide Web, Volume (thermodynamics), Data mining, Information retrieval, Human–computer interaction, Web navigation

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