Journal article
A methodology to allow rural extension professionals to build target-specific expert systems for Australian rural business operators
Expert Systems with Applications, Vol.36(1), pp.735-744
2009
Abstract
Expert systems (ES) development technology has been used to build rural business applications in the past but these have usually been developed using traditional expert systems shells. This paper introduces a new architecture for the development of a design environment where the domain experts can build a knowledge base for target-specific ES for rural business operators. The system allows rural business operators to use their own knowledge in building their own, target-specific ES for tailored development to their own specific requirements. At this stage, this reusable design environment caters for the Australian dairy industry but in the long run we claim it will be useful for the other livestock based rural industries such as beef cattle and sheep. This approach of developing target-specific ES contributes new knowledge in that it provides a new way of developing decision support by allowing human domain experts to develop relevant ES for different livestock farming business. An evolutionary prototyping approach was employed for initial development of a proof of concept example and as a method of outlining the solution environment. Multiple qualitative data collection methods were engaged to facilitate knowledge acquisition in the domain of milk protein enhancement for dairy operations. This paper also describes the generic development procedure used in this project.
Details
- Title
- A methodology to allow rural extension professionals to build target-specific expert systems for Australian rural business operators
- Authors
- Shah J Miah (Author) - Griffith UniversityDon Kerr (Author) - University of the Sunshine Coast - Faculty of BusinessJ G Gammack (Author) - Griffith University
- Publication details
- Expert Systems with Applications, Vol.36(1), pp.735-744
- Publisher
- Pergamon
- Date published
- 2009
- DOI
- 10.1016/j.eswa.2007.10.022
- ISSN
- 0957-4174
- Copyright note
- Copyright © 2009. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
- Organisation Unit
- University of the Sunshine Coast, Queensland; USC Business School - Legacy
- Language
- English
- Record Identifier
- 99449415402621
- Output Type
- Journal article
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- Computer Science, Artificial Intelligence
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