Abstract:Privacy preservation is becoming a critical issue to data‐mining processes. In practice, a data transformation process is often needed to preserve privacy. However, data transformation would introduce a data quality issue. In this case, the impact on data quality due to the data transformation should be estimated and made clear to the user of the data transformation process. In this article, we consider the problem of k‐anonymization transformation in associative classification. The privacy preservation and da… Show more
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