A Unified Notion of Outliers: Properties and Computation

Proceedings - 3rd International Conference on Knowledge Discovery and Data Mining, KDD 1997

Volumn , Issue , 1997, Pages 219-222

  Knorr, Edwin M ^a   Ng, Raymond T ^a  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; MEDICAL IMAGING; STATISTICS;

CRIMINAL ACTIVITIES; DATA CUBE; DATA MINING SYSTEM; OUTLIER DETECTION SYSTEMS; PROPERTY; SIGNAL-PROCESSING; SINGLE MODULES; SPECTRA'S; STATISTICAL DISTRIBUTION;

DATA MINING;

EID: 85170286889     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

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2. Barnett, V., and Lewis, T. 1994. Outliers in Statistical Data. John Wiley & Sons.
3. Bentley, J. L. 1975. Multidimensional binary search trees used for associative searching. CACM 18(9):509-517.
4. Ester, M.; Kriegel, H.-P.; Sander, J.; and Xu, X. 1996. A density-based algorithm for discovering clusters in large spatial databases with noise. In Proc. KDD, 226-231.
5. Fisher, D. 1987. Knowledge acquisition via incremental conceptual clustering. Machine Learning 2(2): 139-172.
6. Freedman, D.; Pisani, R.; and Purves, R. 1978. Statistics. New York: W.W. Norton.
7. Gray, J.; Bosworth, A.; Layman, A.; and Pirahesh, H. 1995. Data cube: A relational aggregation operator generalizing group-by, cross-tab and sub-totals. Technical Report MSR-TR-95-22, Microsoft Research.
8. Hawkins, D. 1980. Identification of Outliers. London: Chapman and Hall.
9. Kaufman, L., and Rousseeuw, P. 1990. Finding Groups in Data. John Wiley & Sons.
10. Knorr, E. M., and Ng, R. T. 1997. A unified notion of outliers. Unpublished Manuscript, Dept. of Computer Science, University of British Columbia.
11. Ng, R., and Han, J. 1994. Efficient and effective clustering methods for spatial data mining. In Proc. 20th VLDB, 144-155.
12. Zhang, T.; Ramakrishnan, R.; and Livny, M. 1996. Birch: An efficient data clustering method for very large databases. In Proc. ACM SIGMOD, 103-114.