
This Article  
 
Share  
Bibliographic References  
Add to:  
Digg Furl Spurl Blink Simpy Del.icio.us Y!MyWeb  
Search  
 
ASCII Text  x  
Vandana P. Janeja, Vijayalakshmi Atluri, "Random Walks to Identify Anomalous FreeForm Spatial Scan Windows," IEEE Transactions on Knowledge and Data Engineering, vol. 20, no. 10, pp. 13781392, October, 2008.  
BibTex  x  
@article{ 10.1109/TKDE.2008.96, author = {Vandana P. Janeja and Vijayalakshmi Atluri}, title = {Random Walks to Identify Anomalous FreeForm Spatial Scan Windows}, journal ={IEEE Transactions on Knowledge and Data Engineering}, volume = {20}, number = {10}, issn = {10414347}, year = {2008}, pages = {13781392}, doi = {http://doi.ieeecomputersociety.org/10.1109/TKDE.2008.96}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE Transactions on Knowledge and Data Engineering TI  Random Walks to Identify Anomalous FreeForm Spatial Scan Windows IS  10 SN  10414347 SP1378 EP1392 EPD  13781392 A1  Vandana P. Janeja, A1  Vijayalakshmi Atluri, PY  2008 KW  Spatial databases KW  Spatial databases and GIS KW  anomaly detection KW  scan statistics VL  20 JA  IEEE Transactions on Knowledge and Data Engineering ER   
[1] L. Anselin, R. Florax, and S. Rey, “Econometrics for Spatial Models, Recent Advances,” Advances in Spatial Econometrics: Methodology, Tools, and Applications, pp. 125, 2004.
[2] F. Aurenhammer, “Voronoi Diagrams: A Survey of a Fundamental Geometric Data Structure,” ACM Computing Surveys, vol. 23, no. 3, pp. 345405, 1991.
[3] M.N. Barber and B.W. Ninham, Random and Restricted Walks: Theory and Applications. Gordon and Breach Science, 1970.
[4] V. Barnett and T. Lewis, Outliers in Statistical Data, third ed. John Wiley and Sons, 1994.
[5] J. Besag and J. Newell, “The Detection of Clusters in Rare Diseases,” J. Royal Statistical Soc., vol. 154, pp. 143155, 1991.
[6] M.M. Breunig, H.P. Kriegel, R.T. Ng, and J. Sander, “OpticsOf: Identifying Local Outliers,” Proc. Third European Conf. Principles of Data Mining and Knowledge Discovery (PKDD '99), pp. 262270, 1999.
[7] Y. Chen, H.B. Jr., X. Dang, and H. Peng, “DepthBased Novelty Detection and Its Application to Taxonomic Research,” Proc. Seventh IEEE Int'l Conf. Data Mining (ICDM '07), pp. 113122, 2007.
[8] L. Duczmal, M. Kulldorff, and L. Huang, “Evaluation of Spatial Scan Statistics for Irregularly Shaped Clusters,” J. Computational and Graphical Statistics, vol. 15, no. 2, pp. 428442, 2006.
[9] L. Duczmal and A. Renato, “A Simulated Annealing Strategy for the Detection of Arbitrarily Shaped Spatial Clusters,” Computational Statistics and Data Analysis, vol. 45, no. 2, pp. 269286, 2004.
[10] M. Ester, H.P. Kriegel, J. Sander, and X. Xu, “A DensityBased Algorithm for Discovering Clusters in Large Spatial Databases,” Proc. Second Int'l Conf. Knowledge Discovery and Data Mining (KDD '96), pp. 4449, 1996.
[11] A. Getis, “Reflections on Spatial Autocorrelation,” Regional Science and Urban Economics, vol. 37, no. 4, pp. 491496, 2007.
[12] J. Glaz, J. Naus, and S. Wallenstein, Scan Statistics. Springer Verlag Series in Statistics, 2001.
[13] D. Griffith, Spatial Autocorrelation: A Primer. Assoc. of Am. Geographers, 1987.
[14] R. Haining, Spatial Data Analysis: Theory and Practice. Cambridge Univ. Press, 2003.
[15] D. Harel and Y. Koren, “Clustering Spatial Data Using Random Walks,” Proc. Seventh Int'l Conf. Knowledge Discovery and Data Mining (KDD '01), pp. 281286, 2001.
[16] V.S. Iyengar, “On Detecting SpaceTime Clusters,” Proc. 10th ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining (KDD '04), pp. 587592, 2004.
[17] V. Janeja and V. Atluri, “$FS^{3}$ : A Random Walk Based FreeForm Spatial Scan Statistic for Anomalous Window Detection,” Proc. Fifth IEEE Int'l Conf. Data Mining (ICDM '05), pp. 661664, 2005.
[18] V. Janeja and V. Atluri, “$LS^{3}$ : A Linear Semantic Scan Statistic Technique for Detecting Anomalous Windows,” Proc. 20th Ann. ACM Symp. Applied Computing (SAC), 2005.
[19] Y. Kou, C. Lu, and D. Chen, “Spatial Weighted Outlier Detection,” Proc. Sixth SIAM Int'l Conf. Data Mining (SDM '06), Apr. 2006.
[20] M. Kulldorff, “A Spatial Scan Statistic,” Comm. Statistics—Theory Methods, vol. 26, no. 6, pp. 14811496, 1997.
[21] M. Kulldorff, Spatial Scan Statistics: Models, Calculations, and Applications, 1999.
[22] M. Kulldorff, W. Athas, E. Feuer, B. Miller, and C. Key, “Evaluating Cluster Alarms: A SpaceTime Scan Statistic and Brain Cancer in Los Alamos,” Am. J. Public Health, vol. 88, no. 9, pp. 13771380, 1998.
[23] H. Li and J.F. Reynolds, “A Simulation Experiment to Quantify Spatial Heterogeneity in Categorical Maps,” Ecology, vol. 75, no. 8, pp. 24462455, 1994.
[24] C. Lu, D. Chen, and Y. Kou, “Detecting Spatial Outliers with Multiple Attributes,” Proc. 15th IEEE Int'l Conf. Tools with Artificial Intelligence (ICTAI '03), p. 122, 2003.
[25] C. Lu, Y. Kou, J. Zhao, and L. Chen, “Detecting and Tracking Regional Outliers in Meteorological Data,” Information Science, vol. 177, no. 7, pp. 16091632, 2007.
[26] H.J. Miller, “Tobler's First Law and Spatial Analysis,” Annals of the Assoc. of Am. Geographers, vol. 94, no. 2, pp. 284289, 2004.
[27] J. Naus, “The Distribution of the Size of the Maximum Cluster of Points on the Line,” J. Am. Statistical Assoc., vol. 60, pp. 532538, 1965.
[28] D. Neill, A. Moore, F. Pereira, and T. Mitchell, “Detecting Significant Multidimensional Spatial Clusters,” Advances in Neural Information Processing Systems, vol. 17, pp. 969976, 2005.
[29] NorthJersey.com, “Making a Wasteland: Ford, the Feds, the Mob,” http://www.northjersey.com/specialreports toxiclegacy.html, Oct. 2005, last accessed on July 2008.
[30] A. Okabe, B. Boots, K. Sugihara, and S. Chiu, Spatial Tessellations: Concepts and Applications of Voronoi Diagrams. John Wiley, 2000.
[31] S. Openshaw, “A Mark 1 Geographical Analysis Machine for the Automated Analysis of Point Data Sets,” Int'l J. Geographical Information Science, vol. 1, no. 4, pp. 335358, 1987.
[32] G.P. Patil and C. Tallie, “Geographic and Network Surveillance via Scan Statistics for Critical Area Detection,” Statistical Science, vol. 18, no. 4, pp. 457465, 2003.
[33] L. Premo, “Local Spatial Autocorrelation Statistics Quantify MultiScale Patterns in Distributional Data: An Example from the Maya Lowlands,” J. Archaeological Science, vol. 31, no. 7, pp. 855866, 2004.
[34] S. Shekhar, C.T. Lu, and P. Zhang, “Detecting GraphBased Spatial Outliers: Algorithms and Applications (a Summary of Results),” Proc. ACM SIGKDD '01, pp. 371376, 2001.
[35] J. Shewchuk, “Delaunay Refinement Algorithms for Triangular Mesh Generation,” Computational Geometry: Theory and Applications, vol. 22, no. 13, pp. 2174, 2002.
[36] R. Sibson, “Locally Equiangular Triangulations,” The Computer J., vol. 21, no. 3, pp. 243245, 1978.
[37] P. Sun and S. Chawla, “On Local Spatial Outliers,” Proc. Fourth IEEE Int'l Conf. Data Mining (ICDM '04), pp. 209216, 2004.
[38] T. Tango and K. Takahashi, “A Flexibly Shaped Spatial Scan Statistic for Detecting Clusters,” Int'l J. Health Geographics, vol. 4, no. 11, 2005.
[39] W. Tobler, “A Computer Model Simulation of Urban Growth in the Detroit Region,” Economic Geography, vol. 46, no. 2, pp.234240, 1970.
[40] “Incidence and Mortality Web Based Report,” technical report, US Cancer Statistics Working Group and Dept. of Health and Human Services, Centers for Disease Control and Prevention and Nat'l Cancer Inst., 19992002.
[41] W.F. Athas and C.R. Key, “Los Alamos Cancer Rate Study: Phase I,” final report, New Mexico Dept. of Health, 1993.