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Volumn 17, Issue 8-9, 2004, Pages 1061-1085

Recursive self-organizing network models

Author keywords

Kohonen map; Recursive models; Self organizing map; Sequence processing; Structured data

Indexed keywords

DATA VISUALIZATION; RECURSIVE COMPUTATION; TREE-STRUCTURED DATA;

EID: 9144230256     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neunet.2004.06.009     Document Type: Article
Times cited : (119)

References (74)
  • 1
    • 0033369033 scopus 로고    scopus 로고
    • Exploiting the past and the future in protein secondary structure prediction
    • P. Baldi, S. Brunak, P. Frasconi, G. Pollastri, and G. Soda Exploiting the past and the future in protein secondary structure prediction Bioinformatics 15 11 1999
    • (1999) Bioinformatics , vol.15 , Issue.11
    • Baldi, P.1    Brunak, S.2    Frasconi, P.3    Pollastri, G.4    Soda, G.5
  • 3
    • 0037928080 scopus 로고    scopus 로고
    • A taxonomy for spatiotemporal connectionist networks revisited: The unsupervised case
    • G. Barreto, A. Araújo, and S.C. Kremer A taxonomy for spatiotemporal connectionist networks revisited: The unsupervised case Neural Computation 15 6 2003 1255 1320
    • (2003) Neural Computation , vol.15 , Issue.6 , pp. 1255-1320
    • Barreto, G.1    Araújo, A.2    Kremer, S.C.3
  • 4
    • 0026898892 scopus 로고
    • Quantifying the neighborhood preservation of self-organizing feature maps
    • H.-U. Bauer, and K.R. Pawelzik Quantifying the neighborhood preservation of self-organizing feature maps IEEE Transactions on Neural Networks 3 4 1992 570 579
    • (1992) IEEE Transactions on Neural Networks , vol.3 , Issue.4 , pp. 570-579
    • Bauer, H.-U.1    Pawelzik, K.R.2
  • 5
    • 0031101545 scopus 로고    scopus 로고
    • Growing a hypercubical output space in a self-organizing feature map
    • H.-U. Bauer, and T. Villmann Growing a hypercubical output space in a self-organizing feature map IEEE Transactions on Neural Networks 8 2 1997 218 226
    • (1997) IEEE Transactions on Neural Networks , vol.8 , Issue.2 , pp. 218-226
    • Bauer, H.-U.1    Villmann, T.2
  • 11
    • 0038604094 scopus 로고    scopus 로고
    • Towards incremental parsing of natural language using recursive neural networks
    • F. Costa, P. Frasconi, V. Lombardo, and G. Soda Towards incremental parsing of natural language using recursive neural networks Applied Intelligence 19 1-2 2003
    • (2003) Applied Intelligence , vol.19 , Issue.12
    • Costa, F.1    Frasconi, P.2    Lombardo, V.3    Soda, G.4
  • 12
    • 0042168470 scopus 로고
    • Two or three things that we know about the Kohonen algorithm
    • M. Verleysen D-side Publications
    • M. Cottrell, J.C. Fort, and G. Pags Two or three things that we know about the Kohonen algorithm M. Verleysen European symposium on artificial neural networks 1994 D-side Publications 235 244
    • (1994) European Symposium on Artificial Neural Networks , pp. 235-244
    • Cottrell, M.1    Fort, J.C.2    Pags, G.3
  • 15
    • 0026436795 scopus 로고
    • Self-organizing maps, convergence properties, and energy functions
    • E. Erwin, K. Obermayer, and K. Schulten Self-organizing maps, convergence properties, and energy functions Biological Cybernetics 67 1 1992 47 55
    • (1992) Biological Cybernetics , vol.67 , Issue.1 , pp. 47-55
    • Erwin, E.1    Obermayer, K.2    Schulten, K.3
  • 16
    • 0742301622 scopus 로고    scopus 로고
    • A spatiotemporal memory based on SOMs with activity diffusion
    • E. Oja S. Kaski Elsevier Amsterdam
    • N.R. Euliano, and J.C. Principe A spatiotemporal memory based on SOMs with activity diffusion E. Oja S. Kaski Kohonen maps 1999 Elsevier Amsterdam
    • (1999) Kohonen Maps
    • Euliano, N.R.1    Principe, J.C.2
  • 20
    • 0032165969 scopus 로고    scopus 로고
    • A general framework for adaptive processing of data structures
    • P. Frasconi, M. Gori, and A. Sperduti A general framework for adaptive processing of data structures IEEE TNN 9 5 1998 768 786
    • (1998) IEEE TNN , vol.9 , Issue.5 , pp. 768-786
    • Frasconi, P.1    Gori, M.2    Sperduti, A.3
  • 23
    • 0033317370 scopus 로고    scopus 로고
    • On the implementation of frontier-to-root tree automata in recursive neural networks
    • M. Gori, A. Küchler, and A. Sperduti On the implementation of frontier-to-root tree automata in recursive neural networks IEEE Transactions on Neural Networks 10 1999
    • (1999) IEEE Transactions on Neural Networks , vol.10
    • Gori, M.1    Küchler, A.2    Sperduti, A.3
  • 26
    • 0038452110 scopus 로고    scopus 로고
    • A supervised self-organizing map for structured data
    • N. Allison H. Yin L. Allinson J. Slack Springer Berlin
    • M. Hagenbuchner, A.C. Tsoi, and A. Sperduti A supervised self-organizing map for structured data N. Allison H. Yin L. Allinson J. Slack Advances in self-organizing maps 2001 Springer Berlin 21 28
    • (2001) Advances in Self-organizing Maps , pp. 21-28
    • Hagenbuchner, M.1    Tsoi, A.C.2    Sperduti, A.3
  • 27
    • 0005946863 scopus 로고    scopus 로고
    • Learning with recurrent neural networks
    • Springer Berlin
    • B. Hammer Learning with recurrent neural networks LNCIS 254 2000 Springer Berlin
    • (2000) LNCIS 254
    • Hammer, B.1
  • 28
    • 0042708923 scopus 로고    scopus 로고
    • Recurrent networks for structured data - A unifying approach and its properties
    • B. Hammer Recurrent networks for structured data - A unifying approach and its properties Cognitive Systems Research 3 2 2002 145 165
    • (2002) Cognitive Systems Research , vol.3 , Issue.2 , pp. 145-165
    • Hammer, B.1
  • 30
    • 9144236741 scopus 로고    scopus 로고
    • A general framework for unsupervised processing of structured data
    • M. Verleysen D-side Publications
    • B. Hammer, A. Micheli, and A. Sperduti A general framework for unsupervised processing of structured data M. Verleysen European symposium on artificial neural networks 2002 D-side Publications 389 394
    • (2002) European Symposium on Artificial Neural Networks , pp. 389-394
    • Hammer, B.1    Micheli, A.2    Sperduti, A.3
  • 31
    • 1542786232 scopus 로고    scopus 로고
    • A general framework for unsupervised processing of structured data
    • B. Hammer, A. Micheli, A. Sperduti, and M. Strickert A general framework for unsupervised processing of structured data Neurocomputing 57 2004 3 35
    • (2004) Neurocomputing , vol.57 , pp. 3-35
    • Hammer, B.1    Micheli, A.2    Sperduti, A.3    Strickert, M.4
  • 33
    • 0042326343 scopus 로고    scopus 로고
    • Recurrent neural networks with small weights implement definite memory machines
    • B. Hammer, and P. Tino Recurrent neural networks with small weights implement definite memory machines Neural Computation 15 8 2003 1897 1929
    • (2003) Neural Computation , vol.15 , Issue.8 , pp. 1897-1929
    • Hammer, B.1    Tino, P.2
  • 34
    • 0036791938 scopus 로고    scopus 로고
    • Generalized relevance learning vector quantization
    • B. Hammer, and T. Villmann Generalized relevance learning vector quantization Neural Networks 15 2002 1059 1068
    • (2002) Neural Networks , vol.15 , pp. 1059-1068
    • Hammer, B.1    Villmann, T.2
  • 35
    • 0035506768 scopus 로고    scopus 로고
    • Self-organizing maps, vector quantization, and mixture modeling
    • T. Heskes Self-organizing maps, vector quantization, and mixture modeling IEEE Transactions on Neural Networks 12 2001 1299 1305
    • (2001) IEEE Transactions on Neural Networks , vol.12 , pp. 1299-1305
    • Heskes, T.1
  • 37
    • 85153931963 scopus 로고
    • SARDNET: A self-organizing feature map for sequences
    • G. Tesauro D. Touretzky T. Leen MIT Press
    • D.L. James, and R. Miikkulainen SARDNET: A self-organizing feature map for sequences G. Tesauro D. Touretzky T. Leen Advances in neural information processing systems 7 1995 MIT Press 577 584
    • (1995) Advances in Neural Information Processing Systems 7 , pp. 577-584
    • James, D.L.1    Miikkulainen, R.2
  • 39
    • 0035392549 scopus 로고    scopus 로고
    • Bankruptcy analysis with self-organizing maps in learning metrics
    • S. Kaski Bankruptcy analysis with self-organizing maps in learning metrics IEEE Transactions on Neural Networks 12 2001 936 947
    • (2001) IEEE Transactions on Neural Networks , vol.12 , pp. 936-947
    • Kaski, S.1
  • 40
    • 0001272054 scopus 로고    scopus 로고
    • Bibliography of self-organizing maps, papers: 1981-1997
    • S. Kaski, J. Kangas, and T. Kohonen Bibliography of self-organizing maps, papers: 1981-1997 Neural Computing Surveys. 1 1998 102 350
    • (1998) Neural Computing Surveys. , vol.1 , pp. 102-350
    • Kaski, S.1    Kangas, J.2    Kohonen, T.3
  • 44
    • 84902191947 scopus 로고    scopus 로고
    • Very large two-level SOM for the browsing of newsgroups
    • C. von der Malsburg W. von Seelen J.C. Vorbrüggen B. Sendhoff Springer Berlin
    • T. Kohonen, S. Kaski, K. Lagus, and T. Honkela Very large two-level SOM for the browsing of newsgroups C. von der Malsburg W. von Seelen J.C. Vorbrüggen B. Sendhoff Proceedings of the ICANN96 1996 Springer Berlin 269 274
    • (1996) Proceedings of the ICANN96 , pp. 269-274
    • Kohonen, T.1    Kaski, S.2    Lagus, K.3    Honkela, T.4
  • 45
    • 0036790769 scopus 로고    scopus 로고
    • How to make large self-organizing maps for nonvectorial data
    • T. Kohonen, and R. Sommervuo How to make large self-organizing maps for nonvectorial data Neural Networks 15 8-9 2002 945 952
    • (2002) Neural Networks , vol.15 , Issue.89 , pp. 945-952
    • Kohonen, T.1    Sommervuo, R.2
  • 48
    • 0001117376 scopus 로고    scopus 로고
    • Spatio-temporal connectionist networks: A taxonomy and review
    • S.C. Kremer Spatio-temporal connectionist networks: A taxonomy and review Neural Computation 13 2 2001 249 306
    • (2001) Neural Computation , vol.13 , Issue.2 , pp. 249-306
    • Kremer, S.C.1
  • 50
    • 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
  • 51
    • 0028204732 scopus 로고
    • Topology representing networks
    • T. Martinetz, and K. Schulten Topology representing networks Neural Networks 7 3 1993 507 522
    • (1993) Neural Networks , vol.7 , Issue.3 , pp. 507-522
    • Martinetz, T.1    Schulten, K.2
  • 52
    • 0030286473 scopus 로고    scopus 로고
    • Constructing deterministic finite-state automata in recurrent neural networks
    • C.W. Omlin, and C.L. Giles Constructing deterministic finite-state automata in recurrent neural networks Journal of the ACM 43 6 1996 937 972
    • (1996) Journal of the ACM , vol.43 , Issue.6 , pp. 937-972
    • Omlin, C.W.1    Giles, C.L.2
  • 56
    • 0002129811 scopus 로고    scopus 로고
    • Self-organizing maps in non-euclidean spaces
    • E. Oja S. Kaski Springer Berlin
    • H. Ritter Self-organizing maps in non-euclidean spaces E. Oja S. Kaski Kohonen maps 1999 Springer Berlin 97 108
    • (1999) Kohonen Maps , pp. 97-108
    • Ritter, H.1
  • 58
    • 0002961288 scopus 로고
    • On the stationary state of Kohonen's self-organizing sensory mapping
    • H. Ritter, and K. Schulten On the stationary state of Kohonen's self-organizing sensory mapping Biological Cybernetics 54 1 1986 99 106
    • (1986) Biological Cybernetics , vol.54 , Issue.1 , pp. 99-106
    • Ritter, H.1    Schulten, K.2
  • 59
    • 0036133934 scopus 로고    scopus 로고
    • Clustering based on conditional distribution in an auxiliary space
    • J. Sinkkonen, and S. Kaski Clustering based on conditional distribution in an auxiliary space Neural Computation 14 2002 217 239
    • (2002) Neural Computation , vol.14 , pp. 217-239
    • Sinkkonen, J.1    Kaski, S.2
  • 60
    • 84958976030 scopus 로고    scopus 로고
    • Neural networks for adaptive processing of structured data
    • G. Dorffner H. Bischof K. Hornik Springer Berlin
    • A. Sperduti Neural networks for adaptive processing of structured data G. Dorffner H. Bischof K. Hornik ICANN'2001 2001 Springer Berlin 5 12
    • (2001) ICANN'2001 , pp. 5-12
    • Sperduti, A.1
  • 61
    • 0031145983 scopus 로고    scopus 로고
    • Supervised neural networks for the classification of structures
    • A. Sperduti, and A. Starita Supervised neural networks for the classification of structures IEEE Transactions on Neural Networks 8 3 1997 714 735
    • (1997) IEEE Transactions on Neural Networks , vol.8 , Issue.3 , pp. 714-735
    • Sperduti, A.1    Starita, A.2
  • 62
    • 12144253167 scopus 로고    scopus 로고
    • Neural gas for sequences
    • M. Strickert, and B. Hammer Neural gas for sequences WSOM'03 2003 53 57
    • (2003) WSOM'03 , pp. 53-57
    • Strickert, M.1    Hammer, B.2
  • 64
    • 9144231717 scopus 로고    scopus 로고
    • Unsupervised recursive sequence processing
    • To appear
    • Strickert, M., Hammer, B., & Blohm, S. (2004). Unsupervised recursive sequence processing. To appear in Neurocomputing.
    • (2004) Neurocomputing
    • Strickert, M.1    Hammer, B.2    Blohm, S.3
  • 65
    • 0038392958 scopus 로고    scopus 로고
    • Learning first-pass structural attachment preferences with dynamic grammars and recursive neural networks
    • P. Sturt, F. Costa, V. Lombardo, and P. Frasconi Learning first-pass structural attachment preferences with dynamic grammars and recursive neural networks Cognition 88 2 2003 133 169
    • (2003) Cognition , vol.88 , Issue.2 , pp. 133-169
    • Sturt, P.1    Costa, F.2    Lombardo, V.3    Frasconi, P.4
  • 66
    • 0035365177 scopus 로고    scopus 로고
    • Temporal Kohonen map and recurrent self-organizing map: Analytical and experimental comparison
    • M. Varsta, J. Heikkonen, J. Lampinen, and J. del R. Milán Temporal Kohonen map and recurrent self-organizing map: Analytical and experimental comparison Neural Processing Letters 13 3 2001 237 251
    • (2001) Neural Processing Letters , vol.13 , Issue.3 , pp. 237-251
    • Varsta, M.1    Heikkonen, J.2    Lampinen, J.3    Milán Del, J.R.4
  • 68
    • 0031097231 scopus 로고    scopus 로고
    • Topology preservation in self-organizing feature maps: Exact definition and measurement
    • T. Villmann, R. Der, M. Herrmann, and T. Martinetz Topology preservation in self-organizing feature maps: Exact definition and measurement IEEE Transactions on Neural Networks 8 2 1997 256 266
    • (1997) IEEE Transactions on Neural Networks , vol.8 , Issue.2 , pp. 256-266
    • Villmann, T.1    Der, R.2    Herrmann, M.3    Martinetz, T.4
  • 69
    • 0037379640 scopus 로고    scopus 로고
    • Neural maps in remote sensing image analysis
    • T. Villmann, E. Merenyi, and B. Hammer Neural maps in remote sensing image analysis Neural Networks 16 3-4 2003 389 403
    • (2003) Neural Networks , vol.16 , Issue.34 , pp. 389-403
    • Villmann, T.1    Merenyi, E.2    Hammer, B.3
  • 71
    • 0036790884 scopus 로고    scopus 로고
    • Recursive self-organizing maps
    • T. Voegtlin Recursive self-organizing maps Neural Networks 15 8-9 2002 979 992
    • (2002) Neural Networks , vol.15 , Issue.89 , pp. 979-992
    • Voegtlin, T.1
  • 72
    • 1542535929 scopus 로고    scopus 로고
    • Recursive self-organizing maps
    • N. Allison H. Yin L. Allinson J. Slack Springer Berlin
    • T. Voegtlin, and R.E. Dominey Recursive self-organizing maps N. Allison H. Yin L. Allinson J. Slack Advances in self-organizing maps 2001 Springer Berlin 210 215
    • (2001) Advances in Self-organizing Maps , pp. 210-215
    • Voegtlin, T.1    Dominey, R.E.2
  • 74
    • 0036487278 scopus 로고    scopus 로고
    • Combining flat and structured representations for fingerprint classification with recursive neural networks and support vector machines
    • Y. Yao, G.L. Marcialis, M. Pontil, P. Frasconi, and F. Roli Combining flat and structured representations for fingerprint classification with recursive neural networks and support vector machines Pattern Recognition 36 2 2003 397 406
    • (2003) Pattern Recognition , vol.36 , Issue.2 , pp. 397-406
    • Yao, Y.1    Marcialis, G.L.2    Pontil, M.3    Frasconi, P.4    Roli, F.5


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