An integrated model for next page access prediction

Khalil, Faten and Li, Jiuyong and Wang, Hua (2009) An integrated model for next page access prediction. International Journal of Knowledge and Web Intelligence, 1 (1/2). pp. 48-80. ISSN 1755-8255

Abstract

Accurate next web page prediction benefits many applications, e-business in particular. The most widely used techniques for this purpose are Markov Model, association rules and clustering. However, each of these techniques has its own limitations, especially when it comes to accuracy and space complexity. This paper presents an improved prediction accuracy and state space complexity by using novel approaches that combine clustering, association rules and Markov Models. The three techniques are integrated together to maximise their strengths. The integration model has been shown to achieve better prediction accuracy than individual and other integrated models.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Permanent restricted access to paper due to publisher copyright restrictions.
Depositing User: Dr Hua Wang
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 31 Jan 2010 10:49
Last Modified: 02 Jul 2013 23:31
Uncontrolled Keywords: web page prediction; Markov Model; association rules; clustering
Fields of Research (FOR2008): 08 Information and Computing Sciences > 0802 Computation Theory and Mathematics > 080201 Analysis of Algorithms and Complexity
Socio-Economic Objective (SEO2008): E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Identification Number or DOI: doi: 10.1504/IJKWI.2009.027925
URI: http://eprints.usq.edu.au/id/eprint/6310

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