Abstract
In this paper we propose an ontology-supported technique to preprocess the remark fields in real-life customer servicing databases in order to discover useful information to help re-categorize misclassified service records owing to human ignorance or bad design of problem categorization. This process restores the database into one with more meaningful data in each record, which facilitates subsequent data analysis. Our experience in applying the technique to a real-life database shows a substantial quality improvement can be obtained in mining association rules from the database. © Springer-Verlag Berlin Heidelberg 2005.
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CITATION STYLE
Chu, B. H., Liao, I. K., & Ho, C. S. (2005). An ontology-supported data preprocessing technique for real-life databases. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3533 LNAI, pp. 521–523). Springer Verlag. https://doi.org/10.1007/11504894_70
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