Skip to main content
SpringerLink
Log in
Book cover

International Conference on Algorithmic Learning Theory

ALT 2011: Algorithmic Learning Theory pp 398–412Cite as

Distributional Learning of Simple Context-Free Tree Grammars

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6925))

Abstract

This paper demonstrates how existing distributional learning techniques for context-free grammars can be adapted to simple context-free tree grammars in a straightforward manner once the necessary notions and properties for string languages have been redefined for trees. Distributional learning is based on the decomposition of an object into a substructure and the remaining structure, and on their interrelations. A corresponding learning algorithm can emulate those relations in order to determine a correct grammar for the target language.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. López, D., Sempere, J.M., García, P.: Inference of reversible tree languages. IEEE Transactions on Systems, Man, and Cybernetics, Part B 34(4), 1658–1665 (2004)

    Article  Google Scholar 

  2. Drewes, F., Högberg, J.: Learning a regular tree language from a teacher. In: Ésik, Z., Fülöp, Z. (eds.) DLT 2003. LNCS, vol. 2710, pp. 279–291. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  3. Besombes, J., Marion, J.Y.: Learning tree languages from positive examples and membership queries. Theoretical Computer Science 382, 183–197 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  4. Oncina, J., Garcia, P.: Inference of recognizable tree sets. Technical report, DSIC II/47/93, Universidad de Valencia (1993)

    Google Scholar 

  5. Shirakawa, H., Yokomori, T.: Polynomial-time MAT learning of c-deterministic context-free grammars. Transaction of Information Processing Society of Japan 34, 380–390 (1993)

    Google Scholar 

  6. Clark, A., Eyraud, R.: Polynomial identification in the limit of substitutable context-free languages. Journal of Machine Learning Research 8, 1725–1745 (2007)

    MathSciNet  MATH  Google Scholar 

  7. Clark, A., Eyraud, R., Habrard, A.: Using contextual representations to efficiently learn context-free languages. Journal of Machine Learning Research 11, 2707–2744 (2010)

    MathSciNet  MATH  Google Scholar 

  8. Clark, A.: Distributional learning of some context-free languages with a minimally adequate teacher. In: [24], pp. 24–37

    Google Scholar 

  9. Clark, A.: Towards general algorithms for grammatical inference. In: Hutter, M., Stephan, F., Vovk, V., Zeugmann, T. (eds.) ALT 2010. LNCS, vol. 6331, pp. 11–30. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  10. Yoshinaka, R.: Efficient learning of multiple context-free languages with multidimensional substitutability from positive data. Theor. Comput. Sci. 412(19), 1821–1831 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  11. Joshi, A.K.: Tree adjoining grammars: How much context-sensitivity is required to provide reasonable structural description. In: Dowty, D., Karttunen, L., Zwicky, A. (eds.) Natural Language Processing, Cambridge University Press, Cambridge (1985)

    Google Scholar 

  12. Yoshinaka, R., Kanazawa, M.: Distributional learning of abstract categorial grammars. In: Pogodalla, S., Prost, J.-P. (eds.) LACL. LNCS, vol. 6736, pp. 251–266. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  13. Comon, H., Dauchet, M., Gilleron, R., Jacquemard, F., Lugiez, D., Tison, S., Tommasi, M.: Tree Automata Techniques and Applications (2008)

    Google Scholar 

  14. Seki, H., Kato, Y.: On the generative power of multiple context-free grammars and macro grammars. IEICE Transactions 91-D(2), 209–221 (2008)

    Article  Google Scholar 

  15. Kanazawa, M., Salvati, S.: The copying power of well-nested multiple context-free grammars. In: Dediu, A.-H., Fernau, H., Martín-Vide, C. (eds.) LATA 2010. LNCS, vol. 6031, pp. 344–355. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  16. Lautemann, C.: The complexity of graph languages generated by hyperedge replacement. Acta. Inf. 27(5), 399–421 (1990)

    Article  MathSciNet  MATH  Google Scholar 

  17. Gold, E.M.: Language identification in the limit. Information and Control 10(5), 447–474 (1967)

    Article  MathSciNet  MATH  Google Scholar 

  18. Clark, A.: Learning context free grammars with the syntactic concept lattice. In: [24], pp. 38–51

    Google Scholar 

  19. Yoshinaka, R.: Towards dual approaches for learning context-free grammars based on syntactic concept lattices. In: Mauri, G., Leporati, A. (eds.) DLT 2011. LNCS, vol. 6795, pp. 429–440. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  20. Habel, A., Kreowski, H.: Some structural aspects of hypergraph languages generated by hyperedge replacement. In: Brandenburg, F.J., Wirsing, M., Vidal-Naquet, G. (eds.) STACS 1987. LNCS, vol. 247, pp. 207–219. Springer, Heidelberg (1987)

    Chapter  Google Scholar 

  21. Clark, A.: Efficient, correct, unsupervised learning of context-sensitive languages. In: Proceedings of CoNLL. Association for Computational Linguistics, Uppsala (2010)

    Google Scholar 

  22. Charniak, E.: Tree-bank grammars. In: Proceedings of the Thirteenth National Conference on Artificial Intelligence, pp. 1031–1036 (1996)

    Google Scholar 

  23. Chen, J., Bangalore, S., Vijay-Shanker, K.: Automated extraction of tree-adjoining grammars from treebanks. Nat. Lang. Eng. 12, 251–299 (2006)

    Article  Google Scholar 

  24. Sempere, J.M., García, P. (eds.): ICGI 2010. LNCS, vol. 6339. Springer, Heidelberg (2010)

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. FB IV Informatik, University of Trier, 54286, Trier

    Anna Kasprzik

  2. ERATO MINATO Project, Japan Science and Technology Agency, Japan

    Ryo Yoshinaka

Authors
  1. Anna Kasprzik
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ryo Yoshinaka
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Helsinki, (Gustaf Hällströmin katu 2b), P.O. Box 68, 00014, Helsinki, Finland

    Jyrki Kivinen  & Esko Ukkonen  & 

  2. Department of Computing Science, University of Alberta, T6G 2E8, Edmonton, AB, Canada

    Csaba Szepesvári

  3. Division of Computer Science, Hokkaido University, N-14, W-9, 060-0814, Sapporo, Japan

    Thomas Zeugmann

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Kasprzik, A., Yoshinaka, R. (2011). Distributional Learning of Simple Context-Free Tree Grammars. In: Kivinen, J., Szepesvári, C., Ukkonen, E., Zeugmann, T. (eds) Algorithmic Learning Theory. ALT 2011. Lecture Notes in Computer Science(), vol 6925. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24412-4_31

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-24412-4_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24411-7

  • Online ISBN: 978-3-642-24412-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation