Toward developing a tele-diagnosis system on fish disease

Autores
Li, Daoliang; Zhu, Wei; Duan, Yanqing; Fu, Zetian
Año de publicación
2006
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Fish disease diagnosis is a complicated process and requires high level of expertise, an expert system for fish disease diagnosis is considered as an effective tool to help fish farmers. However, many farmers have no computers and are not able to access the Internet. Telephone and mobile uses increase rapidly, so, the provision of call centre service appears as a sound alternative support channel for farmer to acquire counseling and support. This paper presents a research attempt to develop and evaluate a call center oriented Hybrid disease diagnosis & consulting system (H-Vet) in aquaculture in China. This paper looks at why H-Vet is needed and what are the advantages and difficulties in the developing and using such a system. A machine learning approach is adopted, which helps to acquire knowledge when enhancing expert systems with the user information collected through call center. This paper also proposes a fuzzy Group Support Systems (GSS) framework for acquiring knowledge from individual expert and aggregating knowledge into workgroup knowledge by H-Vet in the situation of difficult disease diagnosis. The system’s architecture and components are described
IFIP International Conference on Artificial Intelligence in Theory and Practice - Expert Systems
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Expert system tools and techniques
machine learning
Group Decision Support System
call centre
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/23965

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spelling Toward developing a tele-diagnosis system on fish diseaseLi, DaoliangZhu, WeiDuan, YanqingFu, ZetianCiencias InformáticasExpert system tools and techniquesmachine learningGroup Decision Support Systemcall centreFish disease diagnosis is a complicated process and requires high level of expertise, an expert system for fish disease diagnosis is considered as an effective tool to help fish farmers. However, many farmers have no computers and are not able to access the Internet. Telephone and mobile uses increase rapidly, so, the provision of call centre service appears as a sound alternative support channel for farmer to acquire counseling and support. This paper presents a research attempt to develop and evaluate a call center oriented Hybrid disease diagnosis & consulting system (H-Vet) in aquaculture in China. This paper looks at why H-Vet is needed and what are the advantages and difficulties in the developing and using such a system. A machine learning approach is adopted, which helps to acquire knowledge when enhancing expert systems with the user information collected through call center. This paper also proposes a fuzzy Group Support Systems (GSS) framework for acquiring knowledge from individual expert and aggregating knowledge into workgroup knowledge by H-Vet in the situation of difficult disease diagnosis. The system’s architecture and components are describedIFIP International Conference on Artificial Intelligence in Theory and Practice - Expert SystemsRed de Universidades con Carreras en Informática (RedUNCI)2006-08info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/23965enginfo:eu-repo/semantics/altIdentifier/isbn/0-387-34654-6info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-15T10:48:18Zoai:sedici.unlp.edu.ar:10915/23965Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 10:48:19.123SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Toward developing a tele-diagnosis system on fish disease
title Toward developing a tele-diagnosis system on fish disease
spellingShingle Toward developing a tele-diagnosis system on fish disease
Li, Daoliang
Ciencias Informáticas
Expert system tools and techniques
machine learning
Group Decision Support System
call centre
title_short Toward developing a tele-diagnosis system on fish disease
title_full Toward developing a tele-diagnosis system on fish disease
title_fullStr Toward developing a tele-diagnosis system on fish disease
title_full_unstemmed Toward developing a tele-diagnosis system on fish disease
title_sort Toward developing a tele-diagnosis system on fish disease
dc.creator.none.fl_str_mv Li, Daoliang
Zhu, Wei
Duan, Yanqing
Fu, Zetian
author Li, Daoliang
author_facet Li, Daoliang
Zhu, Wei
Duan, Yanqing
Fu, Zetian
author_role author
author2 Zhu, Wei
Duan, Yanqing
Fu, Zetian
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Expert system tools and techniques
machine learning
Group Decision Support System
call centre
topic Ciencias Informáticas
Expert system tools and techniques
machine learning
Group Decision Support System
call centre
dc.description.none.fl_txt_mv Fish disease diagnosis is a complicated process and requires high level of expertise, an expert system for fish disease diagnosis is considered as an effective tool to help fish farmers. However, many farmers have no computers and are not able to access the Internet. Telephone and mobile uses increase rapidly, so, the provision of call centre service appears as a sound alternative support channel for farmer to acquire counseling and support. This paper presents a research attempt to develop and evaluate a call center oriented Hybrid disease diagnosis & consulting system (H-Vet) in aquaculture in China. This paper looks at why H-Vet is needed and what are the advantages and difficulties in the developing and using such a system. A machine learning approach is adopted, which helps to acquire knowledge when enhancing expert systems with the user information collected through call center. This paper also proposes a fuzzy Group Support Systems (GSS) framework for acquiring knowledge from individual expert and aggregating knowledge into workgroup knowledge by H-Vet in the situation of difficult disease diagnosis. The system’s architecture and components are described
IFIP International Conference on Artificial Intelligence in Theory and Practice - Expert Systems
Red de Universidades con Carreras en Informática (RedUNCI)
description Fish disease diagnosis is a complicated process and requires high level of expertise, an expert system for fish disease diagnosis is considered as an effective tool to help fish farmers. However, many farmers have no computers and are not able to access the Internet. Telephone and mobile uses increase rapidly, so, the provision of call centre service appears as a sound alternative support channel for farmer to acquire counseling and support. This paper presents a research attempt to develop and evaluate a call center oriented Hybrid disease diagnosis & consulting system (H-Vet) in aquaculture in China. This paper looks at why H-Vet is needed and what are the advantages and difficulties in the developing and using such a system. A machine learning approach is adopted, which helps to acquire knowledge when enhancing expert systems with the user information collected through call center. This paper also proposes a fuzzy Group Support Systems (GSS) framework for acquiring knowledge from individual expert and aggregating knowledge into workgroup knowledge by H-Vet in the situation of difficult disease diagnosis. The system’s architecture and components are described
publishDate 2006
dc.date.none.fl_str_mv 2006-08
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info:eu-repo/semantics/publishedVersion
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url http://sedici.unlp.edu.ar/handle/10915/23965
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/0-387-34654-6
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
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