Interestingness Classification of Association Rules for Master Data

Abstract

High quality of master data is crucial for almost every company and it has become increasingly difficult for domain experts to validate the quality and extract useful information out of master data sets. However, experts are rare and expensive for companies and cannot be aware of all dependencies in the master data sets. In this paper, we introduce a… (More)
DOI: 10.1007/978-3-319-62701-4_18

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Cite this paper

@inproceedings{Han2017InterestingnessCO, title={Interestingness Classification of Association Rules for Master Data}, author={Wei Han and Julio De Melo Borges and Peter Neumayer and Yong Ding and Till Riedel and Michael Beigl}, booktitle={ICDM}, year={2017} }