Integrating recommendation models for improved web page prediction accuracy

Khalil, Faten and Li, Jiuyong and Wang, Hua (2008) Integrating recommendation models for improved web page prediction accuracy. In: ACSC 2008: 31st Australasian Computer Science Conference, 22-25 Jan 2008, Wollongong, Australia.

[img]
Preview
PDF (Published Version)
Khalil_Li_Wang_ACSC2008_PV.pdf

Download (174Kb)

Abstract

[Abstract]: Recent research initiatives have addressed the need for improved performance of Web page prediction accuracy that would profit many applications, e-business in particular. Different Web usage mining frameworks have been implemented for this purpose specifically Association rules, clustering, and Markov model. Each of these frameworks has its own strengths and weaknesses and it has been proved that using each of these frameworks individually does not provide a suitable solution that answers today's Web page prediction needs. This paper endeavors to provide an improved Web page prediction accuracy by using a novel approach that involves integrating clustering, association rules and Markov models according to some constraints. Experimental results prove that this integration provides better prediction accuracy than using each technique individually.


Statistics for USQ ePrint 5903
Statistics for this ePrint Item
Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Published version deposited in accordance with the copyright policy of the publisher. Copyright c 2008, Australian Computer Society, Inc. This pa per appeared at the Thirty-First Australasian Computer Sci- ence Conference (ACSC2008), Wollongong, Australia. Con- ferences in Research and Practice in Information Technology (CRPIT), Vol. 74. Gillian Dobbie and Bernard Mans, Ed. Reproduction for academic, not-for profit purposes permitted provided this text is included.
Depositing User: Dr Hua Wang
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 19 Oct 2009 00:08
Last Modified: 28 Aug 2014 06:46
Uncontrolled Keywords: web page prediction, association rules, clustering, Markov model
Fields of Research (FOR2008): 08 Information and Computing Sciences > 0804 Data Format > 080401 Coding and Information Theory
URI: http://eprints.usq.edu.au/id/eprint/5903

Actions (login required)

View Item Archive Repository Staff Only