Voronoi diagrams—a survey of a fundamental geometric data structure
ACM Computing Surveys (CSUR)
Clustering spatial data using random walks
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
LS3: a Linear Semantic Scan Statistic technique for detecting anomalous windows
Proceedings of the 2005 ACM symposium on Applied computing
Delaunay refinement algorithms for triangular mesh generation
Computational Geometry: Theory and Applications
Secure interoperation for effective data mining in border control and homeland security applications
dg.o '06 Proceedings of the 2006 international conference on Digital government research
Spatial outlier detection in heterogeneous neighborhoods
Intelligent Data Analysis
Anomalous window discovery through scan statistics for linear intersecting paths (SSLIP)
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Spatial outlier detection: random walk based approaches
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
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Often, it is required to identify anomalous windows over a spatial region that reflect unusual rate of occurrence of a specific event of interest. A spatial scan statistic essentially considers a scan window, and identifies anomalous windows by moving the scan window in the region. While spatial scan statistic has been successful, earlier proposals suffer from two limitations: (i) They resrict the scan window to be of a regular shape (e.g., circle, rectangle, cylinder). However, the region of anomaly, in general, is not necessarily of a regular shape. (ii) They take into account autocorrelation among spatial data, but not spatial heterogeneity. As a result, they often result in inaccurate anomalous windows. To address these limitations, we propose a random walk based Free-Form Spatial Scan Statistic (FS鲁). Application of FS鲁 on real datasets has shown that it can identify more refined anomalous windows with better likelihood ratio of it being an anomaly, than those identified by earlier spatial scan statistic approaches.