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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
07/03/2007 |
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Data da última atualização: |
17/01/2020 |
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Autoria: |
OLIVEIRA, S. R. de M.; ZAÏANE, O. R. |
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Afiliação: |
STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA; OSMAR R. ZAÏANE, University of Alberta. |
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Título: |
A unified framework for protecting sensitive association rules in business collaboration. |
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Ano de publicação: |
2006 |
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Fonte/Imprenta: |
International Journal Business Intelligence and Data Mining, v. 1, n. 3, p. 247-287, 2006. |
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DOI: |
https://doi.org/10.1504/IJBIDM.2006.009135 |
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Idioma: |
Inglês |
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Notas: |
Na publicação: Stanley R. M. Oliveira. |
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Conteúdo: |
Abstract. The sharing of association rules has been proven beneficial in business collaboration, but requires privacy safeguards. One may decide to disclose only part of the knowledge and conceal strategic patterns called sensitive rules. The challenge here is how to protect the sensitive rules without losing the benefit of mining. To address this problem, we propose a unified framework that combines: a set of algorithms to protect sensitive knowledge; retrieval facilities to speed up the process of knowledge protecting; and a set of metrics to evaluate the effectiveness of the proposed algorithms in terms of information loss and private information disclosure |
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Palavras-Chave: |
Association rules; Business collaboration; Collaborative projects; Competitive knowledge; conhecimento competitivo; conhecimento sensitivo; Information loss; Knowledge protection; Mineração de dados; Privacy preserving data mining; Privacy safeguards; Private information disclosure; Proteção do conhecimento; Regras de associação; Regras sensitivas; Sensitive knowledge; Sensitive rules. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
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005 2020-01-17
008 2006 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1504/IJBIDM.2006.009135$2DOI
100 1 $aOLIVEIRA, S. R. de M.
245 $aA unified framework for protecting sensitive association rules in business collaboration.$h[electronic resource]
260 $c2006
500 $aNa publicação: Stanley R. M. Oliveira.
520 $aAbstract. The sharing of association rules has been proven beneficial in business collaboration, but requires privacy safeguards. One may decide to disclose only part of the knowledge and conceal strategic patterns called sensitive rules. The challenge here is how to protect the sensitive rules without losing the benefit of mining. To address this problem, we propose a unified framework that combines: a set of algorithms to protect sensitive knowledge; retrieval facilities to speed up the process of knowledge protecting; and a set of metrics to evaluate the effectiveness of the proposed algorithms in terms of information loss and private information disclosure
653 $aAssociation rules
653 $aBusiness collaboration
653 $aCollaborative projects
653 $aCompetitive knowledge
653 $aconhecimento competitivo
653 $aconhecimento sensitivo
653 $aInformation loss
653 $aKnowledge protection
653 $aMineração de dados
653 $aPrivacy preserving data mining
653 $aPrivacy safeguards
653 $aPrivate information disclosure
653 $aProteção do conhecimento
653 $aRegras de associação
653 $aRegras sensitivas
653 $aSensitive knowledge
653 $aSensitive rules
700 1 $aZAÏANE, O. R.
773 $tInternational Journal Business Intelligence and Data Mining$gv. 1, n. 3, p. 247-287, 2006.
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| 1. |  | ROCHA, L. C.; DUARTE, R. A.; BUSTAMANTE, F. O.; TORRES, G. A.; MITTELMANN, A.; TECHIO, V. H. Characterization of fragile sites in Lolium perenne L. In: PLANT SCIENCE STUDENT CONFERENCE, 10., 2014, Gatersleben. Program & abstracts. Gatersleben: Institut für Pflanzengenetik und Kulturpflanzenforschung, 2014.| Tipo: Resumo em Anais de Congresso |
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