Please use this identifier to cite or link to this item:
|Title:||Correlation-based attribute outlier detection in XML|
|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|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 14, 2017
WEB OF SCIENCETM
checked on Nov 18, 2017
checked on Dec 10, 2017
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.