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FS3: a random walk based free-form spatial scan statistic for anomalous window detection
Janeja, V.P.; Atluri, V.;
Data Mining, Fifth IEEE International Conference on
27-30 Nov. 2005
Page(s):4 pp.
Abstract:
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 restrict 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 (FS3). Application of FS3 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.
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