Detecting Data Errors with Employing Negative Association Rules

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Provided by: AICIT
Topic: Big Data
Format: PDF
Ever increasing amount of data has led to the fact that the data quality has had a crucial impact on almost any IT applications. Nonetheless, data quality issues are nearly omnipresent. Recently, a great deal of researches has focused on improving data quality. Bad quality of the data can cause incorrect decision making. It is normally infeasible to guarantee sufficient data quality through manual inspection. Therefore (semi-)automatic data cleansing methods have to be employed. Data mining methods are ideal for this purpose, since they are aimed at finding abnormal patterns in large volumes of data.
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