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- W2750100897 abstract "The privacy preserving microdata sharing literature has proposed several techniques that allow a database administrator to share a dataset in a privacy preserving manner. This paper considers the implications of adding a market layer to that setting. In this setting, individuals (data providers) can receive a market-determined compensation in exchange for their information while they also receive a personalized privacy protection. The computational burdens of satisfying a variety of privacy requirements of individuals (sellers) and dataset requirements of the data receiver (buyer) are analyzed in this paper. The author presents a polynomial time reformulation procedure that proves that the “optimum information product” creation problem reduces to multiple-choice knapsack problem, which is a weakly NP hard problem. The problem of various instance sizes is solved using FICO Xpress 7.0 optimization software. The insights presented in the paper can be utilized for creating a market of individual information in different settings." @default.
- W2750100897 created "2017-08-31" @default.
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- W2750100897 date "2017-10-01" @default.
- W2750100897 modified "2023-09-25" @default.
- W2750100897 title "Algorithms for Selecting the Optimum Dataset While Providing Personalized Privacy and Compensation to its Participants" @default.
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- W2750100897 doi "https://doi.org/10.4018/ijoris.2017100103" @default.
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