A Call Center System based on Expert Systems for the Acquisition of Agricultural Knowledge Transferred from Text-to-Speech in China. (17th February 2021)
- Record Type:
- Journal Article
- Title:
- A Call Center System based on Expert Systems for the Acquisition of Agricultural Knowledge Transferred from Text-to-Speech in China. (17th February 2021)
- Main Title:
- A Call Center System based on Expert Systems for the Acquisition of Agricultural Knowledge Transferred from Text-to-Speech in China
- Authors:
- Dong, Yuhong
Fu, Zetian
Stankovski, Stevan
Peng, Yaoqi
Li, Xinxing - Abstract:
- Abstract: There is rich knowledge in expert systems that can be used to solve practical problems, but its promotion and application must rely on information facilities. The application of both computers and the Internet for Chinese farmers are not common, which leads to restrictions on the promotion and application of expert systems in rural areas of China. On the other hand, the existing call centers lack a professional knowledge base and the method of automatically calling the knowledge base in real-time, which makes it difficult to meet the needs of users wanting to obtain knowledge in a timely manner. To address these problems, a call center embedded in an expert system inference algorithm and knowledge base for farmers to obtain agricultural knowledge through mobile phones or fixed-line telephones was established. By studying the event-condition-action-based (ECA-based) database triggering model, remote method invocation-based (RMI-based) communication and iterative dichotomiser 3 algorithm-based (ID3-based) parameter extraction, the cohesion between the call center and the expert system was realized. The agricultural knowledge audio acquisition model was then coupled with the call center and the expert system was constructed, allowing farmers to acquire agricultural knowledge through mobile phones or fixed phones with fast responses. When used for cotton disease diagnosis, it can achieve a high diagnostic success rate (above 75%) when at least three disease symptomsAbstract: There is rich knowledge in expert systems that can be used to solve practical problems, but its promotion and application must rely on information facilities. The application of both computers and the Internet for Chinese farmers are not common, which leads to restrictions on the promotion and application of expert systems in rural areas of China. On the other hand, the existing call centers lack a professional knowledge base and the method of automatically calling the knowledge base in real-time, which makes it difficult to meet the needs of users wanting to obtain knowledge in a timely manner. To address these problems, a call center embedded in an expert system inference algorithm and knowledge base for farmers to obtain agricultural knowledge through mobile phones or fixed-line telephones was established. By studying the event-condition-action-based (ECA-based) database triggering model, remote method invocation-based (RMI-based) communication and iterative dichotomiser 3 algorithm-based (ID3-based) parameter extraction, the cohesion between the call center and the expert system was realized. The agricultural knowledge audio acquisition model was then coupled with the call center and the expert system was constructed, allowing farmers to acquire agricultural knowledge through mobile phones or fixed phones with fast responses. When used for cotton disease diagnosis, it can achieve a high diagnostic success rate (above 75%) when at least three disease symptoms are input into the expert system via the voice call, which provides an effective channel for Chinese farmers to obtain agricultural knowledge. It presents good application prospects in China, where 5G technology is currently developing rapidly. … (more)
- Is Part Of:
- Computer journal. Volume 64:Number 6(2021)
- Journal:
- Computer journal
- Issue:
- Volume 64:Number 6(2021)
- Issue Display:
- Volume 64, Issue 6 (2021)
- Year:
- 2021
- Volume:
- 64
- Issue:
- 6
- Issue Sort Value:
- 2021-0064-0006-0000
- Page Start:
- 895
- Page End:
- 908
- Publication Date:
- 2021-02-17
- Subjects:
- expert systems -- call center system -- agricultural knowledge -- text-to-speech
Computers -- Periodicals
005.1 - Journal URLs:
- http://comjnl.oxfordjournals.org/ ↗
http://ukcatalogue.oup.com/ ↗ - DOI:
- 10.1093/comjnl/bxaa195 ↗
- Languages:
- English
- ISSNs:
- 0010-4620
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.060000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 17338.xml