A Unified Approach to Spatial Outlier Detection

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, such as local instability. In this paper, we first provide a general definition 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 provide experimental evaluations of our algorithms using a Minneapolis-St. Paul (Twin Cities) traffic data set.

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Document Details

Document Type
Technical Report
Publication Date
Dec 10, 2001
Accession Number
AD1020020

Entities

People

  • Chang-tien Lu
  • Pusheng Zhang
  • Shashi Shekhar

Organizations

  • Department of Computer Science, University of Oxford

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Anomaly Detection
  • Change Detection
  • Computations
  • Computer Science
  • Cost Models
  • Costs
  • Data Sets
  • Detection
  • Identification
  • Normal Distribution

Fields of Study

  • Computer science

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