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Volumn 17, Issue 4, 2012, Pages 419-428

ClustNails: Visual analysis of subspace clusters

Author keywords

Data exploration; Pixel based techniques; Subspace cluster analysis; Visualization

Indexed keywords

CLUSTER BOUNDARIES; DATA EXPLORATION; MULTIDIMENSIONAL DATA; NOVEL VISUALIZATIONS; PIXEL-BASED TECHNIQUES; SUB-SPACE CLUSTERING; SUBSPACE CLUSTERS; USER INTERACTION;

EID: 84876462572     PISSN: 10070214     EISSN: None     Source Type: Journal    
DOI: 10.1109/TST.2012.6297588     Document Type: Article
Times cited : (24)

References (12)
  • 1
    • 67149084291 scopus 로고    scopus 로고
    • Clustering highdimensional data: A survey on subspace clustering, pattern-based clustering, and correlation clustering
    • Kriegel H P, Kröger P, Zimek A. Clustering highdimensional data: A survey on subspace clustering, pattern-based clustering, and correlation clustering. ACM Transactions on Knowledge Discovery from Data (TKDD), 2009, 3(1): 1-58.
    • (2009) ACM Transactions on Knowledge Discovery from Data (TKDD) , vol.3 , Issue.1 , pp. 1-58
    • Kriegel, H.P.1    Kröger, P.2    Zimek, A.3
  • 6
    • 17044376078 scopus 로고    scopus 로고
    • Subspace clustering for high dimensional data: A review
    • Parsons L, Haque E, Liu H. Subspace clustering for high dimensional data: A review. ACM SIGKDD Explorations Newsletter, 2004, 6(1): 90-105.
    • (2004) ACM SIGKDD Explorations Newsletter , vol.6 , Issue.1 , pp. 90-105
    • Parsons, L.1    Haque, E.2    Liu, H.3
  • 7
    • 84865086248 scopus 로고    scopus 로고
    • Evaluating clustering in subspace projections of high dimensional data
    • Müller E, Günnemann S, Assent I, et al. Evaluating clustering in subspace projections of high dimensional data. Proceedings of the VLDB Endowment, 2009, 2(1): 1270-1281.
    • (2009) Proceedings of the VLDB Endowment , vol.2 , Issue.1 , pp. 1270-1281
    • Müller, E.1    Günnemann, S.2    Assent, I.3
  • 10
    • 78650941965 scopus 로고    scopus 로고
    • Finding and visualizing relevant subspaces for clustering high-dimensional astronomical data using connected morphological operators
    • IEEE CS Press
    • Ferdosi B, Buddelmeijer H, Trager S, et al. Finding and visualizing relevant subspaces for clustering high-dimensional astronomical data using connected morphological operators. In: Proceedings of IEEE Symposium on Visual Analytics Science and Technology (VAST). IEEE CS Press, 2010: 35-42.
    • (2010) Proceedings of IEEE Symposium on Visual Analytics Science and Technology (VAST) , pp. 35-42
    • Ferdosi, B.1    Buddelmeijer, H.2    Trager, S.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.