An architecture for collaborative data mining

Detalhes bibliográficos
Autor(a) principal: Francisco Correia
Data de Publicação: 2010
Outros Autores: Rui Camacho, João Correia Lopes
Tipo de documento: Livro
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/10216/67292
Resumo: Collaborative Data Mining (CDM) develops techniques to solve complex problems of data analysis requiring sets of experts in different domains that may be geographically separate. An important issue in CDM is the sharing of experience among the different experts. In this paper we report on a framework that enables users with different expertise to perform data analysis activities and profit, in a collaborative fashion, from expertise and results of other researchers. The collaborative process is supported by web services that seek for relevant knowledge available among the collaborative web sites. We have successfully designed and deployed a prototype for collaborative Data Mining in domains of Molecular Biology and Chemoinformatics.
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spelling An architecture for collaborative data miningCiência de computadores, Engenharia de computadores, Ciências da computação e da informaçãoComputer science, Computer engineering, Computer and information sciencesCollaborative Data Mining (CDM) develops techniques to solve complex problems of data analysis requiring sets of experts in different domains that may be geographically separate. An important issue in CDM is the sharing of experience among the different experts. In this paper we report on a framework that enables users with different expertise to perform data analysis activities and profit, in a collaborative fashion, from expertise and results of other researchers. The collaborative process is supported by web services that seek for relevant knowledge available among the collaborative web sites. We have successfully designed and deployed a prototype for collaborative Data Mining in domains of Molecular Biology and Chemoinformatics.20102010-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://hdl.handle.net/10216/67292engFrancisco CorreiaRui CamachoJoão Correia Lopesinfo: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:RCAAP2023-11-29T15:52:47Zoai:repositorio-aberto.up.pt:10216/67292Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:34:28.245599Repositório 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 An architecture for collaborative data mining
title An architecture for collaborative data mining
spellingShingle An architecture for collaborative data mining
Francisco Correia
Ciência de computadores, Engenharia de computadores, Ciências da computação e da informação
Computer science, Computer engineering, Computer and information sciences
title_short An architecture for collaborative data mining
title_full An architecture for collaborative data mining
title_fullStr An architecture for collaborative data mining
title_full_unstemmed An architecture for collaborative data mining
title_sort An architecture for collaborative data mining
author Francisco Correia
author_facet Francisco Correia
Rui Camacho
João Correia Lopes
author_role author
author2 Rui Camacho
João Correia Lopes
author2_role author
author
dc.contributor.author.fl_str_mv Francisco Correia
Rui Camacho
João Correia Lopes
dc.subject.por.fl_str_mv Ciência de computadores, Engenharia de computadores, Ciências da computação e da informação
Computer science, Computer engineering, Computer and information sciences
topic Ciência de computadores, Engenharia de computadores, Ciências da computação e da informação
Computer science, Computer engineering, Computer and information sciences
description Collaborative Data Mining (CDM) develops techniques to solve complex problems of data analysis requiring sets of experts in different domains that may be geographically separate. An important issue in CDM is the sharing of experience among the different experts. In this paper we report on a framework that enables users with different expertise to perform data analysis activities and profit, in a collaborative fashion, from expertise and results of other researchers. The collaborative process is supported by web services that seek for relevant knowledge available among the collaborative web sites. We have successfully designed and deployed a prototype for collaborative Data Mining in domains of Molecular Biology and Chemoinformatics.
publishDate 2010
dc.date.none.fl_str_mv 2010
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url https://hdl.handle.net/10216/67292
dc.language.iso.fl_str_mv eng
language eng
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