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2012 | OriginalPaper | Chapter

Use Rule Based to Predict Dirty Values

Authors : Kalaivany Natarajan, Jiuyong Li, Andy Koronios

Published in: Engineering Asset Management and Infrastructure Sustainability

Publisher: Springer London

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Abstract

Nowadays business organizations and large companies are dealing with huge datasets. A main problem with these datasets is dirty data. Dirty data reduce the quality of information management. Data quality is improved by data cleaning. In data cleaning process dirty data are predicted by various mechanisms. Rule based is one of the main techniques for predicting dirty values. Rule based is a human understandable and easily interpretable method. In this paper we build a classifier using association rules to predict dirty values in large datasets. Our classifier is built from multiple target rules (MTR) to identify dirty data. MTR are an extension of association rules.

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Metadata
Title
Use Rule Based to Predict Dirty Values
Authors
Kalaivany Natarajan
Jiuyong Li
Andy Koronios
Copyright Year
2012
Publisher
Springer London
DOI
https://doi.org/10.1007/978-0-85729-493-7_53