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Parsing with Connectionist Networks

  • Ajay N. Jain
  • Alex H. Waibel
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 126)

Abstract

Traditional methods employed in parsing natural language have focused on developing powerful formalisms to represent syntactic and semantic structure along with rules for transforming language into these formalisms. The builders of such systems must accurately anticipate and model all of the language constructs that their systems will encounter. In loosely structured domains such as spoken language the task becomes very difficult. Connectionist networks that learn to transform input word sequences into meaningful target representations may be useful in such cases.

Keywords

Noun Phrase Connectionist Network Relative Clause Hide Unit Feature Unit 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Charniak, E., & Santos, E. (1987). A connectionist context-free parser which is not context-free but then it is not really connectionist either. Proceedings of the Ninth Annual Conference of the Cognitive Science Society (pp. 70–77). Seattle, WA: Lawrence Erlbaum.Google Scholar
  2. Cottrell, G. W. (1985). Connectionist parsing. Proceedings of the Seventh Annual Conference of the Cognitive Science Society (pp. 201–211). Irvine, CA: Lawrence Erlbaum.Google Scholar
  3. Cottrell, G. W. (1989). A connectionist approach to word sense disambiguation. San Mateo, CA: Morgan Kaufmann.Google Scholar
  4. Elman, J. L. (1988). Finding structure in time (Tech. Rep. No. 8801). San Diego: University of California, Center for Research in Language.Google Scholar
  5. Fanty, M. (1986). Context-free parsing with connectionist networks. In J. S. Denker (Ed.), AIP Conference Proceedings No. 151. New York: American Institute of Physics.CrossRefGoogle Scholar
  6. Howells, T. (1988). VITAL: A connectionist parser. Proceedings of the Tenth Annual Conference of the Cognitive Science Society (pp. 18–25). Lawrence Erlbaum.Google Scholar
  7. Jain, A. N. (1989). A connectionist architecture for sequential symbolic domains (Tech. Rep. No. CMU-CS-89–187). Pittsburgh, PA: Carnegie Mellon University, School of Computer Science.Google Scholar
  8. Jain, A. N., & Waibel, A. H. (1990). Incremental parsing by modular recurrent connectionist networks. In D. S. Touretzky (Ed.), Advances in neural information processing systems 2. San Mateo, CA: Morgan Kaufmann.Google Scholar
  9. Jordan, M. I. (1986). Serial order: A parallel distributed processing approach (Tech. Rep. No. 8604). San Diego: University of California, Institute for Cognitive Science.Google Scholar
  10. McClelland, J. L., & Kawamoto, A. H. (1986). Mechanisms of sentence processing: Assigning roles to constituents. In J. L. McClelland & D. E. Rumelhart (Eds.), Parallel distributed processing (Vol. 2). MIT Press.Google Scholar
  11. Miikkulainen, R., & Dyer, M. G. (1989). Encoding input/output representations in connectionist cognitive systems. Proceedings of the 1988 Connectionist Models Summer School (pp. 347–356). Morgan Kaufmann.Google Scholar
  12. Nakamura, M., & Shikano, K. (1989). A study of English word category prediction based on neural networks. Proceedings of the 1989 IEEE International Conference on Acoustic, Speech, and Signal Processing (Vol. S) (pp. 731–734).Google Scholar
  13. Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986). Learning internal representations by error propagation. In D. E. Rumelhart & J. L. McClelland (Eds.), Parallel distributed processing (Vol. 1). The MIT Press.Google Scholar
  14. Selman, B., & Hirst, G. (1985). A rule-based connectionist parsing system. Proceedings of the Seventh Annual Conference of the Cognitive Science Society (pp. 212–221). Irvine, CA: Lawrence Erlbaum.Google Scholar
  15. Waltz, D., & Pollack, J. (1985). Massively parallel parsing: A strongly interactive model of natural language interpretation. Cognitive Science, 9, 51–74.Google Scholar

Copyright information

© Springer Science+Business Media New York 1991

Authors and Affiliations

  • Ajay N. Jain
    • 1
  • Alex H. Waibel
    • 1
  1. 1.School of Computer ScienceCarnegie Mellon UniversityUSA

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