NDLI: A Novel Method for Detecting Outlying Subspaces in High-dimensional Databases Using Genetic Algorithm

Content Provider	IEEE Xplore Digital Library
Author	Ji Zhang Qigang Gao Hai Wang
Copyright Year	2006
Description	Author affiliation: Fac. of Comput. Sci., Dalhousie Univ., Halifax, NS (Ji Zhang; Qigang Gao)
Abstract	Detecting outlying subspaces is a relatively new research problem in outlier-ness analysis for high-dimensional data. An outlying subspace for a given data point p is the sub- space in which p is an outlier. Outlying subspace detection can facilitate a better characterization process for the detected outliers. It can also enable outlier mining for high- dimensional data to be performed more accurately and efficiently. In this paper, we proposed a new method using genetic algorithm paradigm for searching outlying subspaces efficiently. We developed a technique for efficiently computing the lower and upper bounds of the distance between a given point and its $k^{th}$ nearest neighbor in each possible subspace. These bounds are used to speed up the fitness evaluation of the designed genetic algorithm for outlying subspace detection. We also proposed a random sampling technique to further reduce the computation of the genetic algorithm. The optimal number of sampling data is specified to ensure the accuracy of the result. We show that the proposed method is efficient and effective in handling outlying subspace detection problem by a set of experiments conducted on both synthetic and real-life datasets.
Starting Page	731
Ending Page	740
File Size	319327
Page Count	10
File Format	PDF
ISBN	0769527017
ISSN	15504786
DOI	10.1109/ICDM.2006.6
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-12-18
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Genetic algorithms Data mining Algorithm design and analysis Sampling methods Spatial databases Credit cards Computer science Data analysis Upper bound Nearest neighbor searches
Content Type	Text
Resource Type	Article

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