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Volumn , Issue , 2001, Pages 293-298

Mining top-n local outliers in large databases

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTATIONAL METHODS; DATABASE SYSTEMS; PROBLEM SOLVING; THEOREM PROVING; TREES (MATHEMATICS);

EID: 0035788909     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/502512.502554     Document Type: Conference Paper
Times cited : (284)

References (10)
  • 7
    • 0002948319 scopus 로고    scopus 로고
    • Algorithms for mining distance-based outliers in large datasets
    • New York, NY, Aug.
    • E. Knorr and R. Ng. Algorithms for mining distance-based outliers in large datasets. In Proc. 1998 Int. Conf. Very Large Data Bases (VLDB'98), pages 392-403, New York, NY, Aug. 1998.
    • (1998) Proc. 1998 Int. Conf. Very Large Data Bases (VLDB'98) , pp. 392-403
    • Knorr, E.1    Ng, R.2
  • 8
    • 0003136237 scopus 로고
    • Efficient and effective clustering method for spatial data mining
    • Santiago, Chile, Sept.
    • R. Ng and J. Han. Efficient and effective clustering method for spatial data mining. In Proc. 1994 Int. Conf. Very Large Data Bases (VLDB'94), pages 144-155, Santiago, Chile, Sept. 1994.
    • (1994) Proc. 1994 Int. Conf. Very Large Data Bases (VLDB'94) , pp. 144-155
    • Ng, R.1    Han, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.