Insights from a text mining survey on Expert Systems research from 2000 to 2016
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/16120 |
Resumo: | This study presents a literature analysis using a semiautomated text mining and topic modelling approach of the body of knowledge encompassed in 17 years (2000–2016) of literature published in the Wiley's Expert Systems journal, a key reference in Expert Systems (ESs) research, in a total of 488 research articles. The methodological approach included analysing countries from authors' affiliations, with results emphasizing the relevance of both U.S. and U.K. researchers, with Chinese, Turkish, and Spanish holding also a significant relevance. As a result of the sparsity found on the keywords, one of our goals became to devise a taxonomy for future submissions under 2 core dimensions: ESs' methods and ESs' applications. Finally, through topic modelling, data-driven methods were unveiled as the most relevant, pairing with evaluation methods in its application to managerial sciences, arts, and humanities. Findings also show that most of the application domains are well represented, including health, engineering, energy, and social sciences. |
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Insights from a text mining survey on Expert Systems research from 2000 to 2016Expert SystemsLiterature analysisResearch categorizationResearch evolutionText miningThis study presents a literature analysis using a semiautomated text mining and topic modelling approach of the body of knowledge encompassed in 17 years (2000–2016) of literature published in the Wiley's Expert Systems journal, a key reference in Expert Systems (ESs) research, in a total of 488 research articles. The methodological approach included analysing countries from authors' affiliations, with results emphasizing the relevance of both U.S. and U.K. researchers, with Chinese, Turkish, and Spanish holding also a significant relevance. As a result of the sparsity found on the keywords, one of our goals became to devise a taxonomy for future submissions under 2 core dimensions: ESs' methods and ESs' applications. Finally, through topic modelling, data-driven methods were unveiled as the most relevant, pairing with evaluation methods in its application to managerial sciences, arts, and humanities. Findings also show that most of the application domains are well represented, including health, engineering, energy, and social sciences.John Wiley and Sons2018-06-12T12:06:06Z2019-06-12T00:00:00Z2018-01-01T00:00:00Z20182019-03-08T11:41:41Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/16120eng0266-472010.1111/exsy.12280Cortez, P.Moro, S.Rita, P.King, D.Hall, J.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T17:43:02Zoai:repositorio.iscte-iul.pt:10071/16120Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:20:12.465476Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Insights from a text mining survey on Expert Systems research from 2000 to 2016 |
title |
Insights from a text mining survey on Expert Systems research from 2000 to 2016 |
spellingShingle |
Insights from a text mining survey on Expert Systems research from 2000 to 2016 Cortez, P. Expert Systems Literature analysis Research categorization Research evolution Text mining |
title_short |
Insights from a text mining survey on Expert Systems research from 2000 to 2016 |
title_full |
Insights from a text mining survey on Expert Systems research from 2000 to 2016 |
title_fullStr |
Insights from a text mining survey on Expert Systems research from 2000 to 2016 |
title_full_unstemmed |
Insights from a text mining survey on Expert Systems research from 2000 to 2016 |
title_sort |
Insights from a text mining survey on Expert Systems research from 2000 to 2016 |
author |
Cortez, P. |
author_facet |
Cortez, P. Moro, S. Rita, P. King, D. Hall, J. |
author_role |
author |
author2 |
Moro, S. Rita, P. King, D. Hall, J. |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Cortez, P. Moro, S. Rita, P. King, D. Hall, J. |
dc.subject.por.fl_str_mv |
Expert Systems Literature analysis Research categorization Research evolution Text mining |
topic |
Expert Systems Literature analysis Research categorization Research evolution Text mining |
description |
This study presents a literature analysis using a semiautomated text mining and topic modelling approach of the body of knowledge encompassed in 17 years (2000–2016) of literature published in the Wiley's Expert Systems journal, a key reference in Expert Systems (ESs) research, in a total of 488 research articles. The methodological approach included analysing countries from authors' affiliations, with results emphasizing the relevance of both U.S. and U.K. researchers, with Chinese, Turkish, and Spanish holding also a significant relevance. As a result of the sparsity found on the keywords, one of our goals became to devise a taxonomy for future submissions under 2 core dimensions: ESs' methods and ESs' applications. Finally, through topic modelling, data-driven methods were unveiled as the most relevant, pairing with evaluation methods in its application to managerial sciences, arts, and humanities. Findings also show that most of the application domains are well represented, including health, engineering, energy, and social sciences. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-06-12T12:06:06Z 2018-01-01T00:00:00Z 2018 2019-06-12T00:00:00Z 2019-03-08T11:41:41Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/16120 |
url |
http://hdl.handle.net/10071/16120 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0266-4720 10.1111/exsy.12280 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
John Wiley and Sons |
publisher.none.fl_str_mv |
John Wiley and Sons |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799134762090102784 |