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Author Shekhar, Shashi ♦ Lu, Chang-Tien ♦ Zhang, Pusheng
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Spatial Outlier ♦ Detecting Spatial Outlier ♦ Unified Approach ♦ Implicit Knowledge ♦ Computation Structure ♦ General Defiition ♦ Traditional Definition ♦ Detection Method ♦ Twin City ♦ Cost Model ♦ Present Scalable Algorithm ♦ Entire Population ♦ Traffic Data Set ♦ Local Instability
Abstract Spatial outliers represent locations which are significantly different from their neighborhoods even though they may not be significantly different from the entire population. Identification of spatial outliers can lead to the discovery of unexpected, interesting, and implicit knowledge, suchas local instability. In this paper, we first provide a general defiition of S-outliers for spatial outliers. This definition subsumes the traditional definitions of spatial outliers. Second, we characterize the computation structure of spatial outlier detection methods and present scalable algorithms. Third, we provide a cost model of the proposed algorithms. Finally, we experimentally evaluate our algorithms using a Minneapolis-St. Paul (Twin Cities) traffic data set.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Publisher Date 2003-01-01