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Volumn 30, Issue 2, 2001, Pages 37-46

Outlier detection for high dimensional data

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[No Author keywords available]

Indexed keywords


EID: 0038969998     PISSN: 01635808     EISSN: None     Source Type: Journal    
DOI: 10.1145/376284.375668     Document Type: Article
Times cited : (362)

References (27)
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    • Local dimensionality reduction: A new approach to indexing high dimensional spaces
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    • Chakrabarti, K.1    Mehrotra, S.2
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    • A density-based algorithm for discovering clusters in large spatial databases with noise
    • M. Ester, H.-P. Kriegel, J. Sander, X. Xu. A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise. KDD Conference Proceedings, 1996.
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    • Ester, M.1    Kriegel, H.-P.2    Sander, J.3    Xu, X.4
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  • 22
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    • 0012905555 scopus 로고    scopus 로고
    • Finding intensional knowledge of distance-based outliers
    • E. Knorr, R. Ng. Finding Intensional Knowledge of Distance-based Outliers. VLDB Conference Proceedings, 1999.
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    • Knorr, E.1    Ng, R.2
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    • Efficient and effective clustering methods for spatial data mining
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.