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References (cont')

  • V. Hodge and J. Austin. A survey of outlier detection methodologies. Artif. Intell. Rev., 2004.
  • Douglas M Hawkins. Identification of Outliers. Chapman and Hall, 1980.
  • P. S. Horn, L. Feng, Y. Li, and A. J. Pesce. Effect of Outliers and Nonhealthy Individuals on Reference Interval Estimation. Clin Chem, 2001.
  • W. Jin, A. K. H. Tung, J. Han, and W. Wang. Ranking outliers using symmetric neighborhood relationship. PAKDD'06
  • E. Knorr and R. Ng. Algorithms for mining distance-based outliers in large datasets. VLDB’98
  • M. Markou and S. Singh.. Novelty detection: a review| part 1: statistical approaches. Signal Process., 83(12), 2003.
  • M. Markou and S. Singh. Novelty detection: a review| part 2: neural network based approaches. Signal Process., 83(12), 2003.
  • S. Papadimitriou, H. Kitagawa, P. B. Gibbons, and C. Faloutsos. Loci: Fast outlier detection using the local correlation integral. ICDE'03.
  • A. Patcha and J.-M. Park. An overview of anomaly detection techniques: Existing solutions and latest technological trends. Comput. Netw., 51(12):3448{3470, 2007.
  • W. Stefansky. Rejecting outliers in factorial designs. Technometrics, 14(2):469{479, 1972.
  • X. Song, M. Wu, C. Jermaine, and S. Ranka. Conditional anomaly detection. IEEE Trans. on Knowl. and Data Eng., 19(5):631{645, 2007.
  • Y. Tao, X. Xiao, and S. Zhou. Mining distance-based outliers from large databases in any metric space. KDD '06:
  • N. Ye and Q. Chen. An anomaly detection technique based on a chi-square statistic for detecting intrusions into information systems. Quality and Reliability Engineering International, 2001.

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