Abstract
Recently, Augmented Regular Expressions (AREs) have been proposed as a formalism to describe, recognize and learn a nontrivial class of context-sensitive languages (CSLs) [1, 2]. AREs augment the expressive power of Regular Expressions (REs) by including a set of constraints, that involve the number of instances in a string of the operands of the star operations of an RE. Although it is demonstrated that not all the CSLs can be described by AREs, the class of representable objects includes planar shapes with symmetries, which is important for pattern recognition tasks. Likewise, it is proved that AREs cover all the pattern languages [3]. An efficient algorithm is presented to recognize language strings by means of AREs. The method is splitted in two stages: parsing the string by the underlying regular expression and checking that the resulting star instances satisfy the constraints.
Chapter PDF
Similar content being viewed by others
References
R. Alquezar and A. Sanfeliu: ”Augmented regular expressions: a formalism to describe, recognize, and learn a class of context-sensitive languages.” Research Report LSI-95-17-R, Universitat Politecnica de Catalunya, Barcelona, Spain (1995).
R. Alquezar and A. Sanfeliu: Learning of context-sensitive languages described by augmented regular expressions. Proc. 13th Int. Conf. on Pattern Recognition, Aug.1996, Vienna, Austria (1996).
D. Angluin: Finding patterns common to a set of strings. J. Comput. System Science 21, 46–62 (1980).
H.Bunke and A.Sanfeliu (eds): Syntactic and Structural Pattern Recognition: Theory and Applications, World Scientific (1990).
E. Tanaka: Theoretical aspects of syntactic pattern recognition. Pattern Recognition 28, 1053–1061 (1995).
A. Salomaa: Formal Languages, Academic Press, New York (1973).
W.A. Woods: Transition networks grammars for natural language analysis. CACM 13, 591–606 (1970).
S.M. Chou and K.S. Fu: Inference for transition network grammars. Proc. Int. Joint Conf. on Pattern Recognition, 3, CA, 79–84 (1976).
A. Marron and K. Ko: Identification of pattern languages from examples and queries. Information and Computation 74, 91–112 (1987).
Y. Takada: A hierarchy of language families learnable by regular language learners, in Grammatical Inference and Applications, R.C.Carrasco and J.Oncina (eds.). Springer-Verlag, Lecture Notes in Artificial Intelligence 862, 16–24 (1994).
Z. Kohavi: Switching and Finite Automata Theory, (2nd edition). Tata McGraw-Hill, New Delhi, India (1978).
J.E. Hopfcroft and J.D. Ullman: Introduction to Automata Theory, Languages and Computation. Addison-Wesley, Reading MA (1979).
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1996 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Sanfeliu, A., Alquézar, R. (1996). Efficient recognition of a class of context-sensitive languages described by Augmented Regular Expressions. In: Perner, P., Wang, P., Rosenfeld, A. (eds) Advances in Structural and Syntactical Pattern Recognition. SSPR 1996. Lecture Notes in Computer Science, vol 1121. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61577-6_1
Download citation
DOI: https://doi.org/10.1007/3-540-61577-6_1
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-61577-4
Online ISBN: 978-3-540-70631-1
eBook Packages: Springer Book Archive