Abstract
This study aims at providing a hybrid knowledge acquisition approach with fuzzy machine learning technique which assists to obtain knowledge when constructing expert systems. The study defines the knowledge acquisition framework that has been developed in order to make it easier and to provide appropriate interpretations for organic rice farmers and build inferential knowledge based on STEM learning concept in a fuzzy rule representation framework. The main concentration of this study is to demonstrate the knowledge acquisition technique as a method for extending, modernizing and improving a defective knowledge based-system in which fuzzy machine learning is beneficial.
| Original language | English |
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| Title of host publication | Proceedings of the 11th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) |
| Publisher | IEEE |
| Pages | 1-8 |
| Number of pages | 8 |
| ISBN (Electronic) | 9781538646021 |
| ISBN (Print) | 9781538646038 |
| DOIs | |
| Publication status | Published - 8 Dec 2017 |
| Event | 11th International Conference on Software, Knowledge, Information Management and Applications - Sri Lanka Institute of Information Technology, Colombo, Sri Lanka Duration: 6 Dec 2017 → 8 Dec 2017 http://skimanetwork.info/skima2017/ (Conference website) |
Publication series
| Name | |
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| Publisher | IEEE |
| ISSN (Electronic) | 2573-3214 |
Conference
| Conference | 11th International Conference on Software, Knowledge, Information Management and Applications |
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| Abbreviated title | SKIMA 2017 |
| Country/Territory | Sri Lanka |
| City | Colombo |
| Period | 6/12/17 → 8/12/17 |
| Internet address |
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Keywords
- knowledge acquisition
- fuzzy learning rule
- ontology
- STEM
- knowledge representation