Integrating recommendation models for improved web page prediction accuracy

Khalil, Faten and Wang, Hua and Li, Jiuyong (2007) Integrating recommendation models for improved web page prediction accuracy. In: 13th Australasian World Wide Web Conference (AusWeb 2007), 30 June - 4 July 2007, Coffs Harbour, Australia.

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Abstract

[Abstract]: Recent research initiatives have addressed the need for improved performance of Web page prediction that would profit many applications, e-business in particular. Despite the various eforts so far, there is still room for advancement in this field. This paper endeavors to provide an improved prediction accuracy by using a novel approach that involves combining clustering, association rules and Markov models. Each of these frameworks has its own strengths and weaknesses and their integration proves to provide better prediction than using each technique individually.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Deposited in accordance with the copyright policy of the publisher.
Depositing User: Dr Hua Wang
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 19 Feb 2008 02:58
Last Modified: 02 Jul 2013 22:58
Uncontrolled Keywords: web page prediction; accuracy
Fields of Research (FOR2008): 08 Information and Computing Sciences > 0806 Information Systems > 080612 Interorganisational Information Systems and Web Services
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining
08 Information and Computing Sciences > 0807 Library and Information Studies > 080704 Information Retrieval and Web Search
URI: http://eprints.usq.edu.au/id/eprint/3864

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