A web-based interactive data visualization system for outlier subspace analysis

Liu, Dong and Gao, Qigang and Wang, Hai and Zhang, Ji (2010) A web-based interactive data visualization system for outlier subspace analysis. In: SEDE 2010: 19th International Conference on Software Engineering and Data Engineering, 16-18 Jun 2010, San Francisco, CA. United States.

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Abstract

Detecting outliers from high-dimensional data is a
challenge task since outliers mainly reside in various low dimensional subspaces of the data. To tackle this
challenge, subspace analysis based outlier detection
approach has been proposed recently. Detecting outlying
subspaces in which a given data point is an outlier
facilitates a better characterization process for detecting
outliers for high-dimensional data stream, and make
outlier mining for large high-dimensional data set to be
more manageable. In this paper, to facilitate outlier
subspaces analysis from human perception perspectives in
supporting the development of efficient solutions for
high-dimensional data, we propose a web-based
interactive data visualization system, which can display
various low-dimensional outlier subspaces to allow users
to observe and analyze the distributions of outliers. The
proposed visualization tool can help the developers of
outlier detection applications to directly examine the
distributions of outliers in various low-dimensional
subspaces to validate their experiment results.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Publisher: International Society for Computers and Their Applications
Item Status: Live Archive
Additional Information (displayed to public): No evidence of copyright restrictions.
Depositing User: Dr Ji Zhang
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 16 Feb 2011 02:47
Last Modified: 03 Jul 2013 00:27
Uncontrolled Keywords: outliers; subspace analysis; web-based interactive data visualization system
Fields of Research (FoR): 17 Psychology and Cognitive Sciences > 1702 Cognitive Sciences > 170201 Computer Perception, Memory and Attention
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080104 Computer Vision
Socio-Economic Objective (SEO): B Economic Development > 89 Information and Communication Services > 8999 Other Information and Communication Services > 899999 Information and Communication Services not elsewhere classified
URI: http://eprints.usq.edu.au/id/eprint/18207

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