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- W2063938963 abstract "Along with rapid technological advancements, the need for developing suitable frameworks for protecting privacy of individuals becomes essential for the wide-spread acceptance of knowledge-based applications. Privacy Preserving Data Mining has become an active area of research recently to address privacy issues whenever the data is to be provided for a variety of purposes like survey, research etc. Several remarkable frameworks are being developed, but there is not enough sensible solution for considering both privacy and information evenly. Privacy mechanisms which compromise with the information usually weaken the quality of data mining results. An intelligent framework to address this issue is proposed in this paper which also discusses empirical results on classification using original health care data related to Indian population, namely NFHS-3 and shows the effectiveness of our approach." @default.
- W2063938963 created "2016-06-24" @default.
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- W2063938963 date "2014-12-01" @default.
- W2063938963 modified "2023-09-23" @default.
- W2063938963 title "An intelligent framework for protecting privacy of individuals empirical evaluations on data mining classification" @default.
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- W2063938963 doi "https://doi.org/10.1109/his.2014.7086174" @default.
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