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: | 15 Jun 2017 17:52 |
| URI: | http://eprints.covenantuniversity.edu.ng/id/eprint/868 |
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