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Data Quality Mining - Making a Virtue of Necessity - Cornell University - cs cornell

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The document introduces Data Quality Mining (DQM) as a novel approach that utilizes data mining techniques to identify, measure, explain, and rectify data quality issues in large databases. It emphasizes the importance of data quality in Knowledge Discovery in Databases (KDD) and suggests that improving data quality can enhance KDD outcomes while also serving as an independent goal. The paper outlines the potential applications of DQM beyond traditional data analysis and presents a method using association rules to assess data consistency and identify deficiencies.

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