Using Association Rules to Detect Data Quality Issues

نویسندگان

  • Soumaya Ben Hassine
  • Delphine Clément
  • Brigitte Laboisse
چکیده

Since the last decades and due to the high capacity of storage, data is being increasingly available in information society, which has led to the need for valid tools for its modelling and analysis such as Knowledge Discovery in Databases (KDD) methods (known as data mining methods). However, many problems go along with the business application of data mining. In fact, the quality of the generated models is strongly correlated to the data quality. This paper deals with the data mining contribution in the data quality domain, commonly known as DQM; where we used the association rules as a method to improve poor data quality in business databases. We explain our approach and discuss about the results and the possible perspectives.

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تاریخ انتشار 2008