01904naa a2200361 a 450000100080000000500110000800800410001902400520006010000260011224501170013826000090025550000450026452006730030965300220098265300270100465300270103165300260105865300290108465300270111365300210114065300250116165300250118665300350121165300230124665300350126965300310130465300270133565300220136265300240138465300200140870000190142877300950144710082632020-01-17       2006    bl uuuu     u00u1 u    #d7 ahttps://doi.org/10.1504/IJBIDM.2006.0091352DOI1 aOLIVEIRA, S. R. de M.  aA unified framework for protecting sensitive association rules in business collaboration.h[electronic resource]  c2006  aNa publicação: Stanley R. M. Oliveira.  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  aAssociation rules  aBusiness collaboration  aCollaborative projects  aCompetitive knowledge  aconhecimento competitivo  aconhecimento sensitivo  aInformation loss  aKnowledge protection  aMineração de dados  aPrivacy preserving data mining  aPrivacy safeguards  aPrivate information disclosure  aProteção do conhecimento  aRegras de associação  aRegras sensitivas  aSensitive knowledge  aSensitive rules1 aZAÏANE, O. R.  tInternational Journal Business Intelligence and Data Mininggv. 1, n. 3, p. 247-287, 2006.