A Novel Integrated Classifier for Handling Data Warehouse Anomalies

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Title A Novel Integrated Classifier for Handling Data Warehouse Anomalies
Author Darcy, Peter John; Stantic, Bela; Sattar, Abdul
Journal Name Lecture Notes in Computer Science
Editor Johann Elder, Maria Bielikova, A min Tjoa
Year Published 2011
Place of publication Germany
Publisher Springer
Abstract Within databases employed in various commercial sectors, anomalies continue to persist and hinder the overall integrity of data. Typically, Duplicate, Wrong and Missed observations of spatial-temporal data causes the user to be not able to accurately utilise recorded information. In literature, different methods have been mentioned to clean data which fall into the category of either deterministic and probabilistic approaches. However, we believe that to ensure the maximum integrity, a data cleaning methodology must have properties of both of these categories to effectively eliminate the anomalies. To realise this, we have proposed a method which relies both on integrated deterministic and probabilistic classifiers using fusion techniques. We have empirically evaluated the proposed concept with state-of-the-art techniques and found that our approach improves the integrity of the resulting data set.
Peer Reviewed Yes
Published Yes
Alternative URI http://dx.doi.org/10.1007/978-3-642-23737-9_8
Copyright Statement Copyright 2011 Springer Berlin / Heidelberg. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. The original publication is available at www.springerlink.com
Volume 6909
Page from 98
Page to 110
ISSN 0302-9743
Date Accessioned 2012-02-23
Language en_US
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Science, Environment, Engineering and Technology
Subject Coding and Information Theory; Neural, Evolutionary and Fuzzy Computation
URI http://hdl.handle.net/10072/43326
Publication Type Journal Articles (Refereed Article)
Publication Type Code c1

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