An Error-Correcting Parser for a Context-Free Language Based on the Context-Dependent Similarity

  • M. Ikeda
  • E. Tanaka
  • O. Kasusho
Conference paper
Part of the NATO ASI Series book series (volume 45)


Patterns are essentially context-dependent. This paper describes an error-correcting parser for a context-free language, which finds most similar sentences to an input sentence based on the context-dependent similarity(CDS). The proposed algorithm is obtained by modifying the Lyon’s error-correcting parser. Possible application are to the problem of pattern recognition, speech recognition and language processing.


Cost Function Parse Table Error Cost Input Sentence Similar Sentence 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. (1).
    Fu, K.S.: “Error-correcting parsers for syntactic pattern recognition” in DATA Structure, Computer Graphics and Pattern Recognition, Klinger Eds. Academic, N.Y. (1976).Google Scholar
  2. (2).
    Aho, A.V. and Peterson, T.G.: “A minimum distance error-correcting parser for context-free languages”, SIAM J. Comput., 1, pp.305–312 (1972).MathSciNetMATHCrossRefGoogle Scholar
  3. (3).
    Earley, J.:“An efficient context-free parsing algorithm”, CACM, 13, pp.94–102 (1970).MATHGoogle Scholar
  4. (4).
    Lyon, G.:“Syntax-directed least-errors analysis for context-free languages; A practical approach”, Comm. ACM, 17, pp.3–14(1974)MATHCrossRefGoogle Scholar
  5. (5).
    Fung, L.W. and Fu, K.S.: “Maximum-likelihood syntactic decoding”, IEEE Trans. Inf. Theory, IT-21, pp.423–430(1975).MathSciNetCrossRefGoogle Scholar
  6. (6).
    Yamasaki, S. and Tonomura, T.:“On a bottom-up least error correction algorithm for context-free languages”, J. Inf. Process. Soc. Jpn. 18, pp.781–788(1977).Google Scholar
  7. (7).
    Cocke, J. and Schwarts, Y.T.:“Programming language and their compilers”, Courant Inst, of Mathematical Science, N.Y.(1967).Google Scholar
  8. (8).
    Tanaka, E.: “An improved error-correcting parser for a context-free language”, Trans. IECE, Jpn, E-67, 7, pp.379–385(1984).Google Scholar
  9. (9).
    Graham, S.L., Harrison, M.A. and Ruzzo, W.L.:“An improved contextfree recognizer”, ACM Trans. Program. Lang. Syst., 2, pp.415–462(1980).MATHCrossRefGoogle Scholar
  10. (10).
    Levenshtein, B.I.: “Binary codes with correction of deletion, insertion and substitution of symbols”, Dokl. Acak. Nauk. SSSR, l63, pp.845–848(1965).MathSciNetGoogle Scholar
  11. (11).
    Okuda, T., Tanaka, E. and Kasai, T.:“A garbled word correcting method by an extended metric”, Ann. Joint Meeting of Electrical and Electronics Eng. Tokai Distinct, Jpn., 18a-B-6 (1972).Google Scholar
  12. Okuda, T., Tanaka, E. and Kasai, T.: “A method for the correction of garbled words based on Levenshtein metric”, Trans. Comput., C-25, 20, pp.172–178 (1976).MathSciNetCrossRefGoogle Scholar
  13. (12).
    Tanaka, E.: “A context-dependent similarity measure for strings”, Trans. IECE, Jpn, J-67-A, 6, pp.612–613 (1984).Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1988

Authors and Affiliations

  • M. Ikeda
    • 1
  • E. Tanaka
    • 2
  • O. Kasusho
    • 1
  1. 1.The Ins. of Sci. and Ind. Res.Osaka Univ.Ibaraki-Shi, 565Japan
  2. 2.Fac. of EngineeringUtsunomiya Univ.Utsunomiya-Shi, 321Japan

Personalised recommendations