Abstract
Clickstream can be a rich source of data for analysing user behaviour, but the volume of these logs makes it difficult to identify and categorise behavioural patterns. In this paper, we introduce the Automatic Pattern Discovery (APD) method, a technique for automated processing of Clickstream data to identify a user’s browsing patterns. The paper also includes case study that is used to illustrate the use of the APD and to evaluate its performance.
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Ting, IH., Clark, L., Kimble, C., Kudenko, D., Wright, P. (2007). APD-A Tool for Identifying Behavioural Patterns Automatically from Clickstream Data. In: Apolloni, B., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2007. Lecture Notes in Computer Science(), vol 4693. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74827-4_9
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DOI: https://doi.org/10.1007/978-3-540-74827-4_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74826-7
Online ISBN: 978-3-540-74827-4
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