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A Fuzzy Association Rule Mining Expert-Driven (FARME-D) approach to Knowledge Acquisition

Oladipupo, O. O. and Ayo, C. K. and Uwadia, C. O. (2012) A Fuzzy Association Rule Mining Expert-Driven (FARME-D) approach to Knowledge Acquisition. African Journal of Computing & ICT, 5 (5). pp. 53-60. ISSN 2006-1781

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Abstract

Fuzzy Association Rule Mining Expert-Driven (FARME-D) approach to knowledge acquisition is proposed in this paper as a viable solution to the challenges of rule-based unwieldiness and sharp boundary problem in building a fuzzy rule-based expert system. The fuzzy models were based on domain experts’ opinion about the data description. The proposed approach is committed to modelling of a compact Fuzzy Rule-Based Expert Systems. It is also aimed at providing a platform for instant update of the knowledge-base in case new knowledge is discovered. The insight to the new approach strategies and underlining assumptions, the structure of FARME-D and its practical application in medical domain was discussed. Also, the modalities for the validation of the FARME-D approach were discussed.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User: Mr Adewole Adewumi
Date Deposited: 29 Nov 2012 01:36
Last Modified: 29 Nov 2012 01:36
URI: http://eprints.covenantuniversity.edu.ng/id/eprint/868

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