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1 mai 2009
- handle: 10670/1.lkxsmw
- halshs: halshs-00488083
- doi: 10.1504/IJWET.2009.032255
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info:eu-repo/semantics/altIdentifier/doi/10.1504/IJWET.2009.032255
Mots-clés
navigation behaviour web usage mining clickstream data sequential mining web navigation navigation patterns automatic pattern discovery educational website technical support websiteSujets proches
Navigation, PrimitiveCiter ce document
I-Hsien Ting et al., « Identifying web navigation behaviour and patterns automatically from clickstream data », HAL-SHS : sciences de l'information, de la communication et des bibliothèques, ID : 10.1504/IJWET.2009.032255
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Résumé
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.