Search:
Computing and Library Services - delivering an inspiring information environment

Associative text categorisation rules pruning method

Abu-Mansour, Hussein, Hadi, Wa’el , McCluskey, T.L. and Thabtah, Fadi (2010) Associative text categorisation rules pruning method. In: Linguistic And Cognitive Approaches To Dialog Agents Symposium, AISB 2010 Convention, 29 March – 1 April 2010, De Montfort University, Leicester, UK. (Unpublished)

[img] PDF
Abu-Mansour.pdf - Accepted Version
Restricted to Repository staff only

Download (254kB)

Abstract

In this paper, the problem of rule pruning in associative text categorisation is investigated. We propose a new rule pruning method within an existing associative classification algorithm
called MCAR. Experimental results against large text collection (Reuters-21578) using the developed pruning method as well as other known existing methods (Database coverage, lazy pruning)
are conducted. The bases of the experiments are the classification accuracy and the number of generated rules. The results derived show that the proposed rule pruning method derives higher quality and more scalable classifiers than those produced by lazy and database coverage pruning approaches. In addition, the number of rules generated by the developed pruning procedure is usually less than those of lazy pruning and database coverage heuristics.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Schools: School of Computing and Engineering
School of Computing and Engineering > Pedagogical Research Group
School of Computing and Engineering > High-Performance Intelligent Computing
School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge
School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge
Related URLs:
Depositing User: Cherry Edmunds
Date Deposited: 12 Apr 2010 13:22
Last Modified: 15 Jun 2011 08:36
URI: http://eprints.hud.ac.uk/id/eprint/7395

Downloads

Downloads per month over past year

Repository Staff Only: item control page

View Item View Item

University of Huddersfield, Queensgate, Huddersfield, HD1 3DH Copyright and Disclaimer All rights reserved ©