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Volumn 2, Issue 1, 2012, Pages 86-97

Algorithms for hierarchical clustering: An overview

Author keywords

[No Author keywords available]

Indexed keywords

CONFORMAL MAPPING; HIERARCHICAL CLUSTERING; SELF ORGANIZING MAPS;

EID: 84864660152     PISSN: 19424787     EISSN: 19424795     Source Type: Journal    
DOI: 10.1002/widm.53     Document Type: Article
Times cited : (1294)

References (69)
  • 2
    • 0020720613 scopus 로고
    • Techniques for structuring database records
    • March ST. Techniques for structuring database records. ACM Comput Surv 1983, 15:45-79.
    • (1983) ACM Comput Surv , vol.15 , pp. 45-79
    • March, S.T.1
  • 4
    • 0001715023 scopus 로고
    • A review of hierarchical classification
    • Gordon AD. A review of hierarchical classification. J R Stat Soc A 1987, 150:119-137.
    • (1987) J R Stat Soc A , vol.150 , pp. 119-137
    • Gordon, A.D.1
  • 7
    • 16444383160 scopus 로고    scopus 로고
    • Survey of clustering algorithms
    • Xu R, Wunsch D. Survey of clustering algorithms. IEEE Trans Neural Netw 2005, 16:645-678.
    • (2005) IEEE Trans Neural Netw , vol.16 , pp. 645-678
    • Xu, R.1    Wunsch, D.2
  • 11
    • 0021496227 scopus 로고
    • Hierarchic agglomerative clustering methods for automatic document classification
    • Griffiths A, Robinson LA, Willett P. Hierarchic agglomerative clustering methods for automatic document classification. J Doc 1984, 40:175-205.
    • (1984) J Doc , vol.40 , pp. 175-205
    • Griffiths, A.1    Robinson, L.A.2    Willett, P.3
  • 12
    • 70350073872 scopus 로고    scopus 로고
    • Symmetry in data mining and analysis: a unifying view based on hierarchy
    • Murtagh F. Symmetry in data mining and analysis: a unifying view based on hierarchy. Proc Steklov Inst Math 2009, 265:177-198.
    • (2009) Proc Steklov Inst Math , vol.265 , pp. 177-198
    • Murtagh, F.1
  • 18
    • 0002726668 scopus 로고
    • On the history of the minimum spanning tree problem
    • Graham RH, Hell P. On the history of the minimum spanning tree problem. Ann Hist Comput 1985, 7:43- 57.
    • (1985) Ann Hist Comput , vol.7 , pp. 43-57
    • Graham, R.H.1    Hell, P.2
  • 22
    • 34250832748 scopus 로고    scopus 로고
    • The Haar wavelet transform of a dendrogram
    • Murtagh F. The Haar wavelet transform of a dendrogram. J Classif 2007, 24:3-32.
    • (2007) J Classif , vol.24 , pp. 3-32
    • Murtagh, F.1
  • 23
    • 0001831117 scopus 로고
    • Mode analysis: a generalization of nearest neighbour which reduces chaining effects
    • Cole AJ, ed. New York: Academic Press
    • Wishart D. Mode analysis: a generalization of nearest neighbour which reduces chaining effects. In: Cole AJ, ed. Numerical Taxonomy. New York: Academic Press; 1969, 282-311.
    • (1969) Numerical Taxonomy. , pp. 282-311
    • Wishart, D.1
  • 24
    • 0002663098 scopus 로고
    • SLINK: an optimally efficient algorithm for the single link cluster method
    • Sibson R. SLINK: an optimally efficient algorithm for the single link cluster method. Comput J 1973, 16:30- 34.
    • (1973) Comput J , vol.16 , pp. 30-34
    • Sibson, R.1
  • 25
    • 0002344931 scopus 로고
    • Algorithm 76 hierarchical clustering using the minimum spanning tree
    • Rohlf FJ. Algorithm 76: hierarchical clustering using the minimum spanning tree. Comput J 1973, 16:93- 95.
    • (1973) Comput J , vol.16 , pp. 93-95
    • Rohlf, F.J.1
  • 26
    • 0001765146 scopus 로고
    • An efficient algorithm for a complete link method
    • Defays D. An efficient algorithm for a complete link method. Comput J 1977, 20:364-366.
    • (1977) Comput J , vol.20 , pp. 364-366
    • Defays, D.1
  • 27
    • 0001974728 scopus 로고
    • La classification hiěrarchique ascendante selon la měthode des voisins rěciproques
    • de Rham C. La classification hiěrarchique ascendante selon la měthode des voisins rěciproques. Les Cahiers de l'Analyse des Donněes 1980, V:135-144.
    • (1980) Les Cahiers de l'Analyse des Donněes , vol.135-144
    • de Rham, C.1
  • 28
    • 0040586206 scopus 로고
    • Programme de classification hiěrarchique par l'algorithme de la recherche en châ i{dotless}ne des voisins rěciproques
    • Juan J. Programme de classification hiěrarchique par l'algorithme de la recherche en châ i{dotless}ne des voisins rěciproques. Les Cahiers de l'Analyse des Donněes 1982, VII:219-225.
    • (1982) Les Cahiers de l'Analyse des Donněes , vol.2 , pp. 219-225
    • Juan, J.1
  • 29
    • 0020848951 scopus 로고
    • A survey of recent advances in hierarchical clustering algorithms
    • Murtagh F. A survey of recent advances in hierarchical clustering algorithms. Comput J 1983, 26:354-359.
    • (1983) Comput J , vol.26 , pp. 354-359
    • Murtagh, F.1
  • 31
    • 15944395866 scopus 로고
    • Měthodes nouvelles en classification automatique des donněes taxinomiques nombreuses
    • Bruynooghe M. Měthodes nouvelles en classification automatique des donněes taxinomiques nombreuses. Statistique et Analyse des Donněes 1977, 3:24-42.
    • (1977) Statistique et Analyse des Donněes , vol.3 , pp. 24-42
    • Bruynooghe, M.1
  • 32
    • 0000034040 scopus 로고
    • Complexities of hierarchic clustering algorithms: state of the art
    • Murtagh F. Complexities of hierarchic clustering algorithms: state of the art. Comput Stat Quart 1984, 1:101-113.
    • (1984) Comput Stat Quart , vol.1 , pp. 101-113
    • Murtagh, F.1
  • 33
    • 0002546287 scopus 로고
    • Efficient algorithms for agglomerative hierarchical clustering methods
    • Day WHE, Edelsbrunner H. Efficient algorithms for agglomerative hierarchical clustering methods. J Classif 1984, 1:7-24.
    • (1984) J Classif , vol.1 , pp. 7-24
    • Day, W.H.E.1    Edelsbrunner, H.2
  • 34
    • 0024619684 scopus 로고
    • Efficiency of hierarchic agglomerative clustering using the ICL distributed array processor
    • Willett P. Efficiency of hierarchic agglomerative clustering using the ICL distributed array processor. J Doc 1989, 45:1-45.
    • (1989) J Doc , vol.45 , pp. 1-45
    • Willett, P.1
  • 35
    • 0032269667 scopus 로고    scopus 로고
    • Similarity and dissimilarity methods for processing chemical structure databases
    • Gillet VJ, Wild DJ, Willett P, Bradshaw J. Similarity and dissimilarity methods for processing chemical structure databases. Comput J 1998, 41:547-558.
    • (1998) Comput J , vol.41 , pp. 547-558
    • Gillet, V.J.1    Wild, D.J.2    Willett, P.3    Bradshaw, J.4
  • 39
    • 21844508468 scopus 로고
    • The Kohonen selforganizing map method: an assessment
    • Murtagh F, Herńandez-Pajares M. The Kohonen selforganizing map method: an assessment. J Classif 1995, 12:165-190.
    • (1995) J Classif , vol.12 , pp. 165-190
    • Murtagh, F.1    Herńandez-Pajares, M.2
  • 40
    • 0001153915 scopus 로고
    • Clustering properties of hierarchical self-organizing maps
    • Lampinen J, Oja E. Clustering properties of hierarchical self-organizing maps. J Math Imaging Vision 1992, 2:261-272.
    • (1992) J Math Imaging Vision , vol.2 , pp. 261-272
    • Lampinen, J.1    Oja, E.2
  • 41
    • 0036826330 scopus 로고    scopus 로고
    • Uncovering the hierarchical structure in data using the growing hierarchical self-organizing map
    • Dittenbach M, Rauber A, Merkl D. Uncovering the hierarchical structure in data using the growing hierarchical self-organizing map. Neurocomputing, 2002, 48:199-216.
    • (2002) Neurocomputing , vol.48 , pp. 199-216
    • Dittenbach, M.1    Rauber, A.2    Merkl, D.3
  • 42
    • 0036690072 scopus 로고    scopus 로고
    • A clustering method using hierarchical self-organizing maps
    • Endo M, Ueno M, Tanabe T. A clustering method using hierarchical self-organizing maps. J VLSI Signal Process 2002, 32:105-118.
    • (2002) J VLSI Signal Process , vol.32 , pp. 105-118
    • Endo, M.1    Ueno, M.2    Tanabe, T.3
  • 43
    • 0002320685 scopus 로고
    • Script recognition with hierarchical feature maps
    • Miikkulainien R. Script recognition with hierarchical feature maps. Connect Sci 1990, 2:83-101.
    • (1990) Connect Sci , vol.2 , pp. 83-101
    • Miikkulainien, R.1
  • 44
    • 79851486528 scopus 로고    scopus 로고
    • Review of hierarchical models for data clustering and visualization
    • Gir ́ aldez R, Riquelme JC, Aguilar-Ruiz JS, eds. Seville, Spain: Red Espa{ogonek} nola de Mineŕi{dotless}a de Datos;
    • Vicente D, Vellido A. Review of hierarchical models for data clustering and visualization. In: Gir ́ aldez R, Riquelme JC, Aguilar-Ruiz JS, eds. Tendencias de la Mineri{dotless}́a de Datos en Espan{ogonek} a. Seville, Spain: Red Espa {ogonek} nola de Mineŕi{dotless}a de Datos; 2004.
    • (2004) Tendencias de la Mineri{dotless}́a de Datos en Espan{ogonek} a.
    • Vicente, D.1    Vellido, A.2
  • 45
    • 0036565797 scopus 로고    scopus 로고
    • Hierarchical GTM: constructing localized non-linear projection manifolds in a principled way
    • Tino P, Nabney I. Hierarchical GTM: constructing localized non-linear projection manifolds in a principled way. IEEE Trans Pattern Anal Mach Intell 2002, 24:639-656.
    • (2002) IEEE Trans Pattern Anal Mach Intell , vol.24 , pp. 639-656
    • Tino, P.1    Nabney, I.2
  • 46
    • 0034187075 scopus 로고    scopus 로고
    • Probabilistic principal component subspaces: a hierarchical finite mixture model for data visualization
    • Wang Y, Freedman MI, Kung S-Y. Probabilistic principal component subspaces: a hierarchical finite mixture model for data visualization. IEEE Trans Neural Netw 2000, 11:625-636.
    • (2000) IEEE Trans Neural Netw , vol.11 , pp. 625-636
    • Wang, Y.1    Freedman, M.I.2    Kung, S.-Y.3
  • 47
    • 17444368072 scopus 로고    scopus 로고
    • Bayesian inference for multiband image segmentation via model-based clustering trees
    • Murtagh F, Raftery AE, Starck JL. Bayesian inference for multiband image segmentation via model-based clustering trees. Image Vision Comput 2005, 23:587- 596.
    • (2005) Image Vision Comput , vol.23 , pp. 587-596
    • Murtagh, F.1    Raftery, A.E.2    Starck, J.L.3
  • 48
    • 34548583274 scopus 로고    scopus 로고
    • A tutorial on spectral clustering
    • von Luxburg U. A tutorial on spectral clustering. Stat Comput 1997, 17:395-416.
    • (1997) Stat Comput , vol.17 , pp. 395-416
    • von Luxburg, U.1
  • 49
    • 0016932303 scopus 로고
    • Valeurs propres et vecteurs propres en classification hiěrarchique
    • Gondran M. Valeurs propres et vecteurs propres en classification hiěrarchique. RAIRO Informatique Thěorique 1976, 10:39-46.
    • (1976) RAIRO Informatique Thěorique , vol.10 , pp. 39-46
    • Gondran, M.1
  • 50
    • 67949110882 scopus 로고    scopus 로고
    • Clustering, IEEE Computer Society Press
    • Xu R, Wunsch DC. Clustering. IEEE Computer Society Press; 2008.
    • (2008)
    • Xu, R.1    Wunsch, D.C.2
  • 53
    • 0000835955 scopus 로고    scopus 로고
    • Optimal grid-clustering: towards breaking the curse of dimensionality in highdimensional clustering
    • San Francisco, CA: Morgan Kaufmann Publishers Inc.
    • Hinneburg A, Keim D. Optimal grid-clustering: towards breaking the curse of dimensionality in highdimensional clustering. In: VLDB '99: Proceedings of the 25th International Conference on Very Large Data Bases. San Francisco, CA: Morgan Kaufmann Publishers Inc.; 1999, 506-517.
    • (1999) VLDB '99: Proceedings of the 25th International Conference on Very Large Data Bases , pp. 506-517
    • Hinneburg, A.1    Keim, D.2
  • 54
    • 41949141213 scopus 로고    scopus 로고
    • Data Clustering Theory, Algorithms, and Applications
    • Philadelphia PA: SIAM;
    • Gan G, Ma C, Wu J. Data Clustering Theory, Algorithms, and Applications. Philadelphia, PA: SIAM; 2007.
    • (2007)
    • Gan, G.1    Ma, C.2    Wu, J.3
  • 55
    • 84898817460 scopus 로고    scopus 로고
    • Grid-clustering: an efficient hierarchical clustering method for very large data sets
    • Washington, D. C. : IEEE Computer Society
    • Schikuta E. Grid-clustering: an efficient hierarchical clustering method for very large data sets. In: ICPR '96: Proceedings of the 13th International Conference on Pattern Recognition.Washington, D.C.: IEEE Computer Society; 1996, 101-105.
    • (1996) ICPR '96: Proceedings of the 13th International Conference on Pattern Recognition , pp. 101-105
    • Schikuta, E.1
  • 56
    • 0034133653 scopus 로고    scopus 로고
    • Wavecluster: a wavelet based clustering approach for spatial data in very large databases
    • Sheikholeslami G, Chatterjee S, Zhang A. Wavecluster: a wavelet based clustering approach for spatial data in very large databases. VLDB J 2000, 8:289- 304.
    • (2000) VLDB J , vol.8 , pp. 289-304
    • Sheikholeslami, G.1    Chatterjee, S.2    Zhang, A.3
  • 57
    • 0036039291 scopus 로고    scopus 로고
    • A new cell-based clustering method for large, high-dimensional data in data mining applications
    • New York: ACM
    • Chang J-W, Jin D-S. A new cell-based clustering method for large, high-dimensional data in data mining applications. In: SAC '02: Proceedings of the 2002 ACM Symposium on Applied Computing. New York: ACM, 2002, 503-507.
    • (2002) SAC '02: Proceedings of the 2002 ACM Symposium on Applied Computing , pp. 503-507
    • Chang, J.-W.1    Jin, D.-S.2
  • 58
    • 14344255219 scopus 로고    scopus 로고
    • Statistical grid-based clustering over data streams
    • Park NH, LeeWS. Statistical grid-based clustering over data streams. SIGMOD Rec 2004, 33:32-37.
    • (2004) SIGMOD Rec , vol.33 , pp. 32-37
    • Park, N.H.1    Lee, W.S.2
  • 60
    • 22044455069 scopus 로고    scopus 로고
    • Density-based clustering in spatial databases: the algorithm GDBSCAN and its applications
    • Sander J, Ester M, Kriegel H-P, Xu X. Density-based clustering in spatial databases: the algorithm GDBSCAN and its applications. Data Min Knowl Discov 1998, 2:169-194.
    • (1998) Data Min Knowl Discov , vol.2 , pp. 169-194
    • Sander, J.1    Ester, M.2    Kriegel, H.P.3    Xu, X.4
  • 61
    • 22844454592 scopus 로고    scopus 로고
    • A fast parallel clustering algorithm for large spatial databases
    • Xu X, J äger J, Kriegel, H-P. A fast parallel clustering algorithm for large spatial databases. Data Min Knowl Discov 1999, 3:263-290.
    • (1999) Data Min Knowl Discov , vol.3 , pp. 263-290
    • Xu, X.1    Jäger, J.2    Kriegel, H.-P.3
  • 67
    • 55549116015 scopus 로고    scopus 로고
    • Hierarchical clustering of massive, high dimensional data sets by exploiting ultrametric embedding
    • Murtagh F, Downs G, Contreras P. Hierarchical clustering of massive, high dimensional data sets by exploiting ultrametric embedding. SIAM J Sci Comput 2008, 30:707-730.
    • (2008) SIAM J Sci Comput , vol.30 , pp. 707-730
    • Murtagh, F.1    Downs, G.2    Contreras, P.3


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