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Author Chang-Tien Lu ♦ Dechang Chen ♦ Yufeng Kou
Sponsorship IEEE Comput. Soc
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2003
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Special computer methods
Subject Keyword Testing ♦ Algorithm design and analysis ♦ Computer science ♦ Detection algorithms ♦ Performance analysis ♦ Biometrics ♦ Pattern analysis ♦ Credit cards ♦ Voting ♦ Weather forecasting
Abstract A spatial outlier is a spatially referenced object whose non-spatial attribute values are significantly different from the values of its neighborhood. Identification of spatial outliers can lead to the discovery of unexpected, interesting, and useful spatial patterns for further analysis. Previous work in spatial outlier detection focuses on detecting spatial outliers with a single attribute. In the paper, we propose two approaches to discover spatial outliers with multiple attributes. We formulate the multi-attribute spatial outlier detection problem in a general way, provide two effective detection algorithms, and analyze their computation complexity. In addition, using a real-world census data, we demonstrate that our approaches can effectively identify local abnormality in large spatial data sets.
Description Author affiliation: Dept. of Comput. Sci., Virginia Polytech. Inst. & State Univ., Falls Church, VA, USA (Chang-Tien Lu)
ISBN 0769520383
ISSN 10823409
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2003-11-05
Publisher Place USA
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 356.58 kB
Page Count 7
Starting Page 122
Ending Page 128

Source: IEEE Xplore Digital Library