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Distributed Representation of Word

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6591))

Abstract

We present a novel method to train the Elman network to learn literal works. This paper reports findings and results during the training process. Both codes and network weights are trained by using this method. The training error can be greatly reduced by iteratively re-encoding all words.

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References

  1. Elman, J.L.: Finding Structure in Time. Cognitive Science 14, 179–211 (1990)

    Article  Google Scholar 

  2. Rumelhart, D.E., Hinton, G.E., Williams, R.J.: Learning Internal Representations by Error Propagation. In: Rumelhart, D.E., McClelland, J.L. (eds.) Parallel Distributed Processing: Explorations in the Microstructure of Cognition, vol. 1, pp. 318–362. MIT Press, Cambridge (1986)

    Google Scholar 

  3. Marcus, G.: Symposium on Cognitive Architecture: The Algebraic Mind. In: Gernsbacher, M.A., Derry, S. (eds.) Proceedings of the 20th Annual Conference of the Cognitive Science Society. Lawrence Erlbaum Associates, Mahwah (1998)

    Google Scholar 

  4. Elman, J.L.: Generalization, Simple Recurrent Networks, and the Emergence of Structure. In: Gernsbacher, M.A., Derry, S. (eds.) Proceedings of the 20th Annual Conference of the Cognitive Science Society. Lawrence Erlbaum Associates, Mahwah (1998)

    Google Scholar 

  5. Liou, C.-Y., Huang, J.-C., Yang, W.-C.: Semantic addressable encoding. In: King, I., Wang, J., Chan, L.-W., Wang, D. (eds.) ICONIP 2006. LNCS, vol. 4232, pp. 183–192. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  6. Liou, C.-Y., Huang, J.-C., Yang, W.-C.: Modeling Word Perception Using the Elman Network. Neurocomputing 71, 3150–3157 (2008)

    Article  Google Scholar 

  7. Seigelmann, H.T.: Neural Networks and Analog Computation: Beyond the Turing Limit. Springer, Heidelberg (1999)

    Book  Google Scholar 

  8. Peter Pan by J. M. Barrie - Project Gutenberg, http://www.gutenberg.org/ebooks/16

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© 2011 Springer-Verlag Berlin Heidelberg

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Huang, JC., Cheng, WC., Liou, CY. (2011). Distributed Representation of Word. In: Nguyen, N.T., Kim, CG., Janiak, A. (eds) Intelligent Information and Database Systems. ACIIDS 2011. Lecture Notes in Computer Science(), vol 6591. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20039-7_17

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  • DOI: https://doi.org/10.1007/978-3-642-20039-7_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20038-0

  • Online ISBN: 978-3-642-20039-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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