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Volumn , Issue , 2011, Pages 297-301

Document clustering using K-means, heuristic K-means and fuzzy C-means

Author keywords

Cluster Evaluation; Document Clustering; Fuzzy C means; Heuristic K means; K means

Indexed keywords

CLUSTER EVALUATION; DATA SETS; DOCUMENT CLUSTERING; FUZZY C MEAN; FUZZY C-MEANS ALGORITHMS; K-MEANS; NEWS ARTICLES; PERFORMANCE MEASURE; STOP WORD; TEXT DOCUMENT; TEXT FILE; UNSUPERVISED CLASSIFICATION;

EID: 84856194303     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CICN.2011.62     Document Type: Conference Paper
Times cited : (75)

References (17)
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  • 12
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    • Classic 4 (7095)
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  • 13
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    • and also at
    • and also at http://www.dataminingresearch.com/download/dataset/ classicdocs.rar
  • 14
    • 84919404904 scopus 로고    scopus 로고
    • -20 Newsgroups Dataset, http://www.ai.mit.edu/prople/jrennie/20- newsgroups/
    • 20 Newsgroups Dataset
  • 15
    • 84948481845 scopus 로고
    • An algorithm for suffix stripping
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    • (1980) Program , vol.14 , Issue.3
    • Porter, M.F.1
  • 17
    • 33749563831 scopus 로고    scopus 로고
    • K-means clustering versus validation measures - A data distribution perspective
    • ACM Press
    • H. Xiong, J. Wu, and J. Chen, "K-means clustering versus validation measures- a data distribution perspective", In KDD'06, ACM Press, 2006.
    • (2006) KDD'06
    • Xiong, H.1    Wu, J.2    Chen, J.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.