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Volumn 2006, Issue , 2006, Pages 619-623

Robust clustering for tracking noisy evolving data streams

Author keywords

Dynamic clustering; Evolving data streams; Robust clustering; Scalable clustering; Stream clustering

Indexed keywords

COMPUTATIONAL METHODS; DATA STRUCTURES; DYNAMIC PROGRAMMING; INFORMATION ANALYSIS;

EID: 33745434153     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1137/1.9781611972764.72     Document Type: Conference Paper
Times cited : (25)

References (11)
  • 1
    • 0038205905 scopus 로고    scopus 로고
    • Requirements for clustering data streams
    • Daniel Barbara, "Requirements for clustering data streams," ACM SIGKDD Explorations Newsletter, vol. 3, no. 2, pp. 23-27, 2002.
    • (2002) ACM SIGKDD Explorations Newsletter , vol.3 , Issue.2 , pp. 23-27
    • Barbara, D.1
  • 2
    • 0001986373 scopus 로고    scopus 로고
    • Continuous queries over data streams
    • S. Babu and J. Widom, "Continuous queries over data streams," in SIGMOD Record'01, 2001, pp. 109-120.
    • (2001) SIGMOD Record'01 , pp. 109-120
    • Babu, S.1    Widom, J.2
  • 11
    • 85140527321 scopus 로고    scopus 로고
    • An efficient approach to clustering in large multimedia databases with noise
    • Alexander Hinneburg and Daniel A. Keim, "An efficient approach to clustering in large multimedia databases with noise," in Knowledge Discovery and Data Mining, 1998, pp. 58-65.
    • (1998) Knowledge Discovery and Data Mining , pp. 58-65
    • Hinneburg, A.1    Keim, D.A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.