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Volumn 1, Issue , 2009, Pages 714-718

A local outlier detection approach based on graph-cut

Author keywords

[No Author keywords available]

Indexed keywords

GRAPH-CUT; K-NEAREST NEIGHBORS; LOCAL OUTLIERS; MINIMUM SPANNING TREES; REAL DATA SETS;

EID: 70649103890     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CSO.2009.272     Document Type: Conference Paper
Times cited : (4)

References (12)
  • 5
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    • Discovering cluster-based local outliers
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    • Z. He, X. Xu, and S. Deng. Discovering cluster-based local outliers. Pattern Recognition Letters, 24(9-10):1641-1650, June 2003.
    • (2003) Pattern Recognition Letters , vol.24 , Issue.9-10 , pp. 1641-1650
    • He, Z.1    Xu, X.2    Deng, S.3
  • 6
    • 0002948319 scopus 로고    scopus 로고
    • Algorithms for mining distancebased outliers in large datasets
    • New York, USA
    • E. M. Knorr and R. T. Ng. Algorithms for mining distancebased outliers in large datasets. In Proceedings of VLDB'98, pages 392-403, New York, USA, 1998.
    • (1998) Proceedings of VLDB'98 , pp. 392-403
    • Knorr, E.M.1    Ng, R.T.2
  • 7
    • 0039845384 scopus 로고    scopus 로고
    • S. Ramaswamy, R. Rastogi, and K. Shim. Efficient algorithms for mining outliers from large data sets. In In Proceedings of the 2000 ACM SIGMOD international conference on Management of data, pages 93-104, Dallas, Texas, 2000.
    • S. Ramaswamy, R. Rastogi, and K. Shim. Efficient algorithms for mining outliers from large data sets. In In Proceedings of the 2000 ACM SIGMOD international conference on Management of data, pages 93-104, Dallas, Texas, 2000.
  • 8
    • 0042323830 scopus 로고    scopus 로고
    • Computing depth contours of bivariate point clouds
    • Novermber
    • I. Ruts and P. Rousseeuwb. Computing depth contours of bivariate point clouds. Computational Statistics & Data Analysis, 23(1):153-168, Novermber 1996.
    • (1996) Computational Statistics & Data Analysis , vol.23 , Issue.1 , pp. 153-168
    • Ruts, I.1    Rousseeuwb, P.2
  • 10
    • 3543125360 scopus 로고    scopus 로고
    • Online unsupervised outlier detection using finite mixtures with discounting learning algorithms
    • May
    • K. Yamanishi, J. Takeuchi, G. Williams, and P. Milne. Online unsupervised outlier detection using finite mixtures with discounting learning algorithms. Data Mining and Knowledge Discovery, 8(5):275-300, May 2004.
    • (2004) Data Mining and Knowledge Discovery , vol.8 , Issue.5 , pp. 275-300
    • Yamanishi, K.1    Takeuchi, J.2    Williams, G.3    Milne, P.4
  • 11
    • 0014976008 scopus 로고
    • Graph-theoretical methods for detecting and describing gestalt clusters
    • January
    • C. T. Zahn. Graph-theoretical methods for detecting and describing gestalt clusters. IEEE Trans. on Computers, C- 20(1):68-86, January 1971.
    • (1971) IEEE Trans. on Computers , vol.C- 20 , Issue.1 , pp. 68-86
    • Zahn, C.T.1
  • 12
    • 40849120409 scopus 로고    scopus 로고
    • Ldbod: A novel local distribution based outlier detector
    • May
    • Y. Zhang, S. Yang, and Y. Wang. Ldbod: A novel local distribution based outlier detector. Pattern Recognition Letters, 29(7):967-976, May 2008.
    • (2008) Pattern Recognition Letters , vol.29 , Issue.7 , pp. 967-976
    • Zhang, Y.1    Yang, S.2    Wang, Y.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.