메뉴 건너뛰기




Volumn 45, Issue 8, 2012, Pages 3034-3044

Vector quantization based approximate spectral clustering of large datasets

Author keywords

CONN similarity; Connectivity; Large datasets; Neural gas; Self organizing maps; Spectral clustering; Vector quantization

Indexed keywords

CONN SIMILARITY; CONNECTIVITY; LARGE DATASETS; NEURAL GAS; SPECTRAL CLUSTERING;

EID: 84859421733     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2012.02.012     Document Type: Article
Times cited : (75)

References (41)
  • 1
    • 67650299342 scopus 로고    scopus 로고
    • Learning highly structured manifolds: Harnessing the power of SOMs
    • M. Biehl, B. Hammer, M. Verleysen, T. Villmann, Springer-Verlag
    • E. Merényi, K. Taşdemir, and L. Zhang Learning highly structured manifolds: harnessing the power of SOMs M. Biehl, B. Hammer, M. Verleysen, T. Villmann, Similarity Based Clustering, Lecture Notes in Artificial Intelligence vol. 5400 2009 Springer-Verlag 138 168
    • (2009) Similarity Based Clustering, Lecture Notes in Artificial Intelligence , vol.5400 , pp. 138-168
    • Merényi, E.1    Taşdemir, K.2    Zhang, L.3
  • 3
    • 84899013108 scopus 로고    scopus 로고
    • On spectral clustering: Analysis and an algorithm
    • T. Dietterich, S. Becker, Z. Ghahramani, MIT Press
    • A. Ng, M. Jordan, and Y. Weiss On spectral clustering: analysis and an algorithm T. Dietterich, S. Becker, Z. Ghahramani, Advances in Neural Information Processing Systems vol. 14 2002 MIT Press
    • (2002) Advances in Neural Information Processing Systems , vol.14
    • Ng, A.1    Jordan, M.2    Weiss, Y.3
  • 5
    • 35448945640 scopus 로고    scopus 로고
    • Spectral clustering with eigenvector selection
    • DOI 10.1016/j.patcog.2007.07.023, PII S0031320307003688, Feature Generation and Machine Learning for Robust Multimodal Biometrics
    • T. Xiang, and S. Gong Spectral clustering with eigenvector selection Pattern Recognition 41 3 2008 1012 1029 (Pubitemid 47632681)
    • (2008) Pattern Recognition , vol.41 , Issue.3 , pp. 1012-1029
    • Xiang, T.1    Gong, S.2
  • 6
    • 73249143874 scopus 로고    scopus 로고
    • Segmentation and classification of polarimetric SAR data using spectral graph partitioning
    • K. Ersahin, I.G. Cumming, and R.K. Ward Segmentation and classification of polarimetric SAR data using spectral graph partitioning IEEE Transactions on Geoscience and Remote Sensing 48 1 2010 164 174
    • (2010) IEEE Transactions on Geoscience and Remote Sensing , vol.48 , Issue.1 , pp. 164-174
    • Ersahin, K.1    Cumming, I.G.2    Ward, R.K.3
  • 7
    • 4243128193 scopus 로고    scopus 로고
    • On clusterings: Good, bad and spectral
    • R. Kannan, S. Vempala, and A. Vetta On clusterings: good, bad and spectral Journal of the ACM 51 3 2004 497 515
    • (2004) Journal of the ACM , vol.51 , Issue.3 , pp. 497-515
    • Kannan, R.1    Vempala, S.2    Vetta, A.3
  • 9
    • 34548583274 scopus 로고    scopus 로고
    • Technical Report TR-149, Max Planck Institute for Biological Cybernetics, March 2007
    • U. von Luxburg, A Tutorial on Spectral Clustering, Technical Report TR-149, Max Planck Institute for Biological Cybernetics, March 2007.
    • A Tutorial on Spectral Clustering
    • Von Luxburg, U.1
  • 10
    • 34548025132 scopus 로고    scopus 로고
    • A survey of kernel and spectral methods for clustering
    • DOI 10.1016/j.patcog.2007.05.018, PII S0031320307002580
    • M. Filippone, F. Camastra, F. Masulli, and S. Rovetta A survey of kernel and spectral methods for clustering Pattern Recognition 41 1 2008 176 190 (Pubitemid 47284212)
    • (2008) Pattern Recognition , vol.41 , Issue.1 , pp. 176-190
    • Filippone, M.1    Camastra, F.2    Masulli, F.3    Rovetta, S.4
  • 13
    • 77957020072 scopus 로고    scopus 로고
    • Enabling scalable spectral clustering for image segmentation
    • F. Tung, A. Wong, and D.A. Clausi Enabling scalable spectral clustering for image segmentation Pattern Recognition 43 12 2010 4069 4076
    • (2010) Pattern Recognition , vol.43 , Issue.12 , pp. 4069-4076
    • Tung, F.1    Wong, A.2    Clausi, D.A.3
  • 16
    • 40049083817 scopus 로고    scopus 로고
    • Selective sampling for approximate clustering of very large data sets
    • DOI 10.1002/int.20268
    • L. Wang, J. Bezdek, C. Leckie, and R. Kotagiri Selective sampling for approximate clustering of very large datasets International Journal of Intelligent Systems 23 3 2008 313 331 (Pubitemid 351322241)
    • (2008) International Journal of Intelligent Systems , vol.23 , Issue.3 , pp. 313-331
    • Wang, L.1    Bezdek, J.C.2    Leckie, C.3    Kotagiri, R.4
  • 18
    • 77957979677 scopus 로고    scopus 로고
    • Approximate pairwise clustering for large data sets via sampling plus extension
    • L. Wang, C. Leckie, R. Kotagiri, and J. Bezdek Approximate pairwise clustering for large data sets via sampling plus extension Pattern Recognition 44 2 2011 222 235
    • (2011) Pattern Recognition , vol.44 , Issue.2 , pp. 222-235
    • Wang, L.1    Leckie, C.2    Kotagiri, R.3    Bezdek, J.4
  • 20
    • 0003410791 scopus 로고    scopus 로고
    • second ed. Springer-Verlag Berlin, Heidelberg
    • T. Kohonen Self-Organizing Maps second ed. 1997 Springer-Verlag Berlin, Heidelberg
    • (1997) Self-Organizing Maps
    • Kohonen, T.1
  • 21
    • 0027632248 scopus 로고
    • Neural gas network for vector quantization and its application to time series prediction
    • T. Martinetz, S. Berkovich, and K. Schulten Neural gas network for vector quantization and its application to time series prediction IEEE Transactions on Neural Networks 4 4 1993 558 569
    • (1993) IEEE Transactions on Neural Networks , vol.4 , Issue.4 , pp. 558-569
    • Martinetz, T.1    Berkovich, S.2    Schulten, K.3
  • 22
    • 34748844548 scopus 로고    scopus 로고
    • Knowledge discovery in urban environments from fused multi-dimensional imagery
    • P. Gamba, M. Crawford, (Eds.) Paris, France, 1113 April 2007, IEEE Catalog number 07EX1577
    • E. Merényi, B. Csathó, K. Taşdemir, Knowledge discovery in urban environments from fused multi-dimensional imagery, in: P. Gamba, M. Crawford, (Eds.), Proceedings of Fourth IEEE GRSS/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas (URBAN 2007), Paris, France, 1113 April 2007, IEEE Catalog number 07EX1577, 2007.
    • (2007) Proceedings of Fourth IEEE GRSS/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas (URBAN 2007)
    • E. Merényi1
  • 23
    • 0037379640 scopus 로고    scopus 로고
    • Neural maps in remote sensing image analysis
    • DOI 10.1016/S0893-6080(03)00021-2
    • T. Villmann, E. Merényi, and B. Hammer Neural maps in remote sensing image analysis Neural Networks, Special Issue on Self-Organizing Maps for Analysis of Complex Scientific Data 34 16 2003 389 403 (Pubitemid 36379090)
    • (2003) Neural Networks , vol.16 , Issue.3-4 , pp. 389-403
    • Villmann, T.1    Merenyi, E.2    Hammer, B.3
  • 24
    • 78649332752 scopus 로고    scopus 로고
    • Local density adaptive similarity measurement for spectral clustering
    • X. Zhang, J. Li, and H. Yu Local density adaptive similarity measurement for spectral clustering Pattern Recognition Letters 32 2 2011 352 358
    • (2011) Pattern Recognition Letters , vol.32 , Issue.2 , pp. 352-358
    • Zhang, X.1    Li, J.2    Yu, H.3
  • 27
    • 24944572401 scopus 로고    scopus 로고
    • Maps for the visualization of high-dimensional data spaces
    • A. Ultsch, Maps for the visualization of high-dimensional data spaces, in: Workshop on Self-Organizing Maps (WSOM), 2003, pp. 225230.
    • (2003) Workshop on Self-Organizing Maps (WSOM) , pp. 225-230
    • Ultsch, A.1
  • 30
    • 34249070931 scopus 로고    scopus 로고
    • Explicit magnification control of self-organizing maps for Forbidden data
    • DOI 10.1109/TNN.2007.895833
    • E. Merényi, A. Jain, and T. Villmann Explicit magnification control of self-organizing maps for forbidden data IEEE Transactions on Neural Networks 18 3 2007 786 797 (Pubitemid 46778096)
    • (2007) IEEE Transactions on Neural Networks , vol.18 , Issue.3 , pp. 786-797
    • Merenyi, E.1    Jain, A.2    Villmann, T.3
  • 31
    • 67349242966 scopus 로고    scopus 로고
    • Exploiting data topology in visualization and clustering of self-organizing maps
    • K. Taşdemir, and E. Merényi Exploiting data topology in visualization and clustering of self-organizing maps IEEE Transactions on Neural Networks 20 4 2009 549 562
    • (2009) IEEE Transactions on Neural Networks , vol.20 , Issue.4 , pp. 549-562
    • Taşdemir, K.1    Merényi, E.2
  • 32
    • 84867175210 scopus 로고    scopus 로고
    • Combining neural gas and learning vector quantization for cursive character recognition
    • DOI 10.1016/S0925-2312(02)00613-6, PII S0925231202006136
    • F. Camastra, and A. Vinciarelli Combining neural gas and learning vector quantization for cursive character recognition Neurocomputing 51 2003 147 159 (Pubitemid 36367230)
    • (2003) Neurocomputing , vol.51 , pp. 147-159
    • Camastra, F.1    Vinciarelli, A.2
  • 33
    • 0028204732 scopus 로고
    • Topology representing networks
    • T. Martinetz, and K. Schulten Topology representing networks Neural Networks 7 3 1994 507 522
    • (1994) Neural Networks , vol.7 , Issue.3 , pp. 507-522
    • Martinetz, T.1    Schulten, K.2
  • 34
    • 77649274978 scopus 로고    scopus 로고
    • Graph based representations of density distribution and distances for self-organizing maps
    • K. Taşdemir Graph based representations of density distribution and distances for self-organizing maps IEEE Transactions on Neural Networks 21 3 2010 520 526
    • (2010) IEEE Transactions on Neural Networks , vol.21 , Issue.3 , pp. 520-526
    • Taşdemir, K.1
  • 36
    • 0036791938 scopus 로고    scopus 로고
    • Generalized relevance learning vector quantization
    • B. Hammer, and T. Villmann Generalized relevance learning vector quantization Neural Networks 15 89 2002 1059 1068
    • (2002) Neural Networks , vol.15 , Issue.89 , pp. 1059-1068
    • Hammer, B.1    Villmann, T.2
  • 38
    • 19344374461 scopus 로고    scopus 로고
    • Self-organizing information fusion and hierarchical knowledge discovery: A new framework using ARTMAP neural networks
    • DOI 10.1016/j.neunet.2004.12.003, PII S089360800400231X
    • G.A. Carpenter, S. Martens, and O.J. Ogas Self-organizing information fusion and hierarchical knowledge discovery: a new framework using ARTMAP neural networks Neural Networks 18 3 2005 287 295 (Pubitemid 40719530)
    • (2005) Neural Networks , vol.18 , Issue.3 , pp. 287-295
    • Carpenter, G.A.1    Martens, S.2    Ogas, O.J.3
  • 40
    • 0347963789 scopus 로고    scopus 로고
    • GTM: The generative topographic mapping
    • C.M. Bishop, M. Svensen, and C.K.I. Williams GTM: the generative topographic mapping Neural Computation 10 1 1998 215 234 (Pubitemid 128463659)
    • (1998) Neural Computation , vol.10 , Issue.1 , pp. 215-234
    • Bishop, C.M.1    Svensen, M.2    Williams, C.K.I.3
  • 41
    • 18544389845 scopus 로고    scopus 로고
    • Enhanced neural gas network for prototype-based clustering
    • DOI 10.1016/j.patcog.2004.12.007, PII S0031320305000208
    • A. Qin, and P. Suganthan Enhanced neural gas network for prototype-based clustering Pattern Recognition 38 8 2005 1275 1288 (Pubitemid 40654775)
    • (2005) Pattern Recognition , vol.38 , Issue.8 , pp. 1275-1288
    • Qin, A.K.1    Suganthan, P.N.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.