Skip to main content
SpringerLink
Log in

Grammar Inference

  • Reference work entry
  • First Online:
Encyclopedia of Database Systems

  • 16 Accesses

Synonyms

Automata induction; Automatic induction; Automatic language induction; Grammar induction; Grammatical induction; Grammatical inference

Definition

Grammar inference is the task of learning grammars or languages from training data. It is a type of inductive inference, the name given to learning techniques that try to guess general rules from examples.

The basic problem is to find a grammar consistent with a training set of positive examples. Usually, the target language is infinite, while the training set is finite. Some work assumes that both positive and negative examples are available, but this is not true in most real applications. Sometimes probability information is attached to each example. In this case, it is possible to learn a probability distribution for the strings in the language in addition to the grammar. This is sometimes called stochastic grammar inference.

A grammar inference algorithm must target a particular grammar representation. More expressive...

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

Access this chapter

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 4,499.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 6,499.99
Price excludes VAT (USA)
  • Durable hardcover 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

Institutional subscriptions

Recommended Reading

  1. Ahonen H, Mannila H, Nikunen E. Generating grammars for SGML tagged texts lacking DTD. In: Proceedings of the Workshop on Principles of Document Processing; 1994.

    Google Scholar 

  2. Ahonen H, Mannila H, Nikunen E. Forming grammars for structured documents: an application of grammatical inference. In: Carrasco R, Oncina J, editors. Lecture notes in computer science, vol. 862. Berlin/New York: Springer; 1994. p. 153–67.

    Google Scholar 

  3. Angluin D. On the complexity of minimum inference of regular sets. Inf Control. 1978;39(3):337–50.

    Article  MathSciNet  MATH  Google Scholar 

  4. Angluin D. Inference of reversible languages. J ACM. 1982;29(3):741–85.

    Article  MathSciNet  MATH  Google Scholar 

  5. Baum LE, Petrie T, Soules G, Weiss N. A maximization technique occurring in the statistical analysis of probabilistic functions of markov chains. Ann Math Stat. 1970;41(1):164–71.

    Article  MathSciNet  MATH  Google Scholar 

  6. Fankhauser P, Xu Y. MarkItUp! an incremental approach to document structure recognition. Electron Publ Orig Dissem Des. 1993;6(4):447–56.

    Google Scholar 

  7. Gold EM. Language identification in the limit. Inf Control. 1967;10(5):447–74.

    Article  MathSciNet  MATH  Google Scholar 

  8. Gold EM. Complexity of automaton identification from finite data. Inf Control. 1978;37(3):302–20.

    Article  MATH  Google Scholar 

  9. Goldman R, Widom J. DataGuides: enabling query formulation and optimization in semi-structured databases. In: Proceedings of the 23th International Conference on Very Large Data Bases; 1997. p. 436–45.

    Google Scholar 

  10. Hopcroft JE, Ullman JD. Introduction to automata theory, languages and computation. Reading: Addison-Wesley; 1979.

    MATH  Google Scholar 

  11. Oncina J, García P. Inferring regular languages in polynomial updated time. In: de la Blanca NP, Sanfeliu A, Vidal E, editors. Pattern recognition and image analysis. Singapore: World Scientific; 1992. p. 49–61.

    Chapter  Google Scholar 

  12. Sánchez JA, Benedí JM. Statistical inductive learning of regular formal languages. In: Carrasco R, Oncina J, editors. Lecture notes in computer science, vol. 862; 1994. p. 130–8.

    Chapter  Google Scholar 

  13. Shafer K. Creating DTDs via the GB-engine and Fred. Dublin/Ohio: OCLC Online Computer Library Center; 1995.

    Google Scholar 

  14. Stolcke A, Omohundro S. Inducing probabilistic grammars by Bayesian model merging. In: Carrasco R, Oncina J, editors. Lecture notes in computer science. 862; 1994. p. 106–18.

    Google Scholar 

  15. Young-Lai M, Tompa FW. Stochastic grammatical inference of text database structure. Mach Learn. 2000;40(2):111–37.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Sybase iAnywhere, Waterloo, ON, Canada

    Matthew Young-Lai

Authors
  1. Matthew Young-Lai
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Matthew Young-Lai .

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, GA, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, ON, Canada

    M. Tamer Özsu

Section Editor information

  1. David R. Cheriton School of Computer Science, Univ. of Waterloo, Waterloo, Ontario, Canada

    Frank Tompa

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Science+Business Media, LLC, part of Springer Nature

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Young-Lai, M. (2018). Grammar Inference. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_182

Download citation

Publish with us

Policies and ethics

Search

Navigation