메뉴 건너뛰기




Volumn , Issue , 2011, Pages 859-867

Algorithms for speeding up distance-based outlier detection

Author keywords

Distributed computing; Nearest neighbor; Outlier detection

Indexed keywords

DISTRIBUTED COMPUTER SYSTEMS; INDEXING (OF INFORMATION); SIGNAL DETECTION; STATISTICS;

EID: 80052650750     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2020408.2020554     Document Type: Conference Paper
Times cited : (80)

References (15)
  • 1
    • 78349238131 scopus 로고    scopus 로고
    • A distributed approach to detect outliers in very large data sets
    • F. Angiulli, S. Basta, S. Lodi, and C. Sartori. A Distributed Approach to Detect Outliers in Very Large Data Sets. In Proocedings of Euro-Par'10, pages 329-340, 2010.
    • (2010) Proocedings of Euro-Par'10 , pp. 329-340
    • Angiulli, F.1    Basta, S.2    Lodi, S.3    Sartori, C.4
  • 2
    • 67149118905 scopus 로고    scopus 로고
    • DOLPHIN: An efficient algorithm for mining distance-based outliers in very large datasets
    • 4:1-4:57
    • F. Angiulli and F. Fassetti. DOLPHIN: An Efficient Algorithm for Mining Distance-based Outliers in Very Large Datasets. ACM TKDD, 3:4:1-4:57, 2009.
    • (2009) ACM TKDD , vol.3
    • Angiulli, F.1    Fassetti, F.2
  • 3
    • 79957798213 scopus 로고    scopus 로고
    • Fast outlier detection in high dimensional spaces
    • F. Angiulli and C. Pizzuti. Fast Outlier Detection in High Dimensional Spaces. In Proceedings of PKDD'02, pages 15-26, 2002.
    • (2002) Proceedings of PKDD'02 , pp. 15-26
    • Angiulli, F.1    Pizzuti, C.2
  • 4
    • 77952380096 scopus 로고    scopus 로고
    • Mining distance-based outliers in near linear time with randomization and a simple pruning rule
    • S. Bay and M. Schwabacher. Mining distance-based outliers in near linear time with randomization and a simple pruning rule. In Proceedings of SIGKDD'03, pages 29-38, 2003.
    • (2003) Proceedings of SIGKDD'03 , pp. 29-38
    • Bay, S.1    Schwabacher, M.2
  • 5
    • 0016557674 scopus 로고
    • Multidimensional binary search trees used for associative searching
    • J. Bentley. Multidimensional binary search trees used for associative searching. Commun. ACM, 18:509-517, 1975.
    • (1975) Commun. ACM , vol.18 , pp. 509-517
    • Bentley, J.1
  • 6
    • 0001802606 scopus 로고    scopus 로고
    • The X-tree : An index structure for high-dimensional data
    • S. Berchtold, D. Keim, and H. Kriegel. The X-tree : An Index Structure for High-Dimensional Data. In Proceedings of VLDB'96, pages 28-39, 1996.
    • (1996) Proceedings of VLDB'96 , pp. 28-39
    • Berchtold, S.1    Keim, D.2    Kriegel, H.3
  • 9
    • 42749086305 scopus 로고    scopus 로고
    • Fast mining of distance-based outliers in high-dimensional datasets
    • A. Ghoting, S. Parthasarathy, and M. Otey. Fast mining of distance-based outliers in high-dimensional datasets. DMKD, 16:349-364, 2008.
    • (2008) DMKD , vol.16 , pp. 349-364
    • Ghoting, A.1    Parthasarathy, S.2    Otey, M.3
  • 11
    • 0036644801 scopus 로고    scopus 로고
    • Parallel mining of outliers in large database
    • DOI 10.1023/A:1015608814486
    • E. Hung and D. Cheung. Parallel Mining of Outliers in Large Database. Distrib. Parallel Databases, 12:5-26, 2002. (Pubitemid 34720972)
    • (2002) Distributed and Parallel Databases , vol.12 , Issue.1 , pp. 5-26
    • Hung, E.1    Cheung, D.W.2
  • 12
    • 0002948319 scopus 로고    scopus 로고
    • Algorithms for mining distance-based outliers in large datasets
    • E. Knorr and R. Ng. Algorithms for Mining Distance-Based Outliers in Large Datasets. In Proceedings of VLDB'98, pages 392-403, 1998.
    • (1998) Proceedings of VLDB'98 , pp. 392-403
    • Knorr, E.1    Ng, R.2
  • 13
    • 34548570503 scopus 로고    scopus 로고
    • Parallel algorithms for distance-based and density-based outliers
    • DOI 10.1109/ICDM.2005.116, 1565768, Proceedings - Fifth IEEE International Conference on Data Mining, ICDM 2005
    • E. Lozano and E. Acuna. Parallel Algorithms for Distance-Based and Density-Based Outliers. In Proceedings of ICDM'05, pages 729-732, 2005. (Pubitemid 47385782)
    • (2005) Proceedings - IEEE International Conference on Data Mining, ICDM , pp. 729-732
    • Lozano, E.1    Acuna, E.2
  • 14
    • 33646553013 scopus 로고    scopus 로고
    • Fast distributed outlier detection in mixed-attribute data sets
    • M. Otey, A. Ghoting, and S. Parthasarathy. Fast Distributed Outlier Detection in Mixed-Attribute Data Sets. DMKD, 12:203-228, 2006.
    • (2006) DMKD , vol.12 , pp. 203-228
    • Otey, M.1    Ghoting, A.2    Parthasarathy, S.3
  • 15
    • 0039845384 scopus 로고    scopus 로고
    • Efficient algorithms for mining outliers from large data sets
    • S. Ramaswamy, R. Rastogi, and K. Shim. Efficient Algorithms for Mining Outliers from Large Data Sets. In Proceedings of SIGMOD'00, pages 427-438, 2000.
    • (2000) Proceedings of SIGMOD'00 , pp. 427-438
    • Ramaswamy, S.1    Rastogi, R.2    Shim, K.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.