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Volumn 78, Issue , 2010, Pages 557-562

An efficient successive iteration partial cluster algorithm for large datasets

Author keywords

cluster analysis; large data set; sampling density; successive iteration partial clustering

Indexed keywords

CLUSTER ALGORITHMS; DATA ITEMS; DATA SETS; LARGE DATA; LARGE DATASETS; SAMPLING DENSITIES; SAMPLING DENSITY; SUCCESSIVE ITERATION; SUCCESSIVE ITERATION PARTIAL CLUSTERING; DATA SET; PARTIAL CLUSTERING;

EID: 80052952912     PISSN: 18675662     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-14880-4_61     Document Type: Conference Paper
Times cited : (4)

References (9)
  • 2
    • 0041965980 scopus 로고    scopus 로고
    • Cluster ensemble a knowledge reuse framework for combining multiple partitions
    • Strehl, Ghosh, J.: Cluster ensemble a knowledge reuse framework for combining multiple partitions. Journal of Machine learning Research 3, 583-617 (2002)
    • (2002) Journal of Machine learning Research , vol.3 , pp. 583-617
    • Strehl Ghosh, J.1
  • 7
    • 0032269108 scopus 로고    scopus 로고
    • How many clusters?Which Clustering Method? Answers via Model-Based Cluster Analysis
    • journal Fraley, C., Raftery, A.E.: How many clusters?Which Clustering Method? Answers via Model-Based Cluster Analysis. The Computer Journal 8, 578-588 (1998)
    • (1998) The Computer Journal , vol.8 , pp. 578-588
    • Journal Fraley, C.1    Raftery, A.E.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.