Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICDE.2008.4497610
Title: Correlation-based attribute outlier detection in XML
Authors: Koh, J.L.Y.
Lee, M.L. 
Hsu, W. 
Ang, W.T.
Issue Date: 2008
Source: Koh, J.L.Y., Lee, M.L., Hsu, W., Ang, W.T. (2008). Correlation-based attribute outlier detection in XML. Proceedings - International Conference on Data Engineering : 1522-1524. ScholarBank@NUS Repository. https://doi.org/10.1109/ICDE.2008.4497610
Abstract: Compared to relational data models, the hierarchical structure of semi structured data such as XML provides semantically meaningful neighbourhoods advancing data cleaning problems such as outlier detection. In this paper, we introduce the concept of correlated subspace that leverages on the hierarchical relationships between XML attributes to provide contextually informative neighbourhoods for attribute outlier detection. We also design two correlation-based attribute outlier metrics for XML, namely the xO-Measure and xQ-Measure. The effectiveness of our XML outlier detection approach Is supported with experimental results. © 2008 IEEE.
Source Title: Proceedings - International Conference on Data Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/40931
ISBN: 9781424418374
ISSN: 10844627
DOI: 10.1109/ICDE.2008.4497610
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