Approximate matching between a context-free grammar and a finite-state automaton

Sang Ki Ko; Yo Sub Han; Kai Salomaa

doi:10.1016/j.ic.2016.02.001

Approximate matching between a context-free grammar and a finite-state automaton

Sang Ki Ko, Yo Sub Han, Kai Salomaa

College of Computing

Research output: Contribution to journal › Article › peer-review

7 Citations (Scopus)

Abstract

For a given context-free grammar (CFG) and a finite-state automaton (FA), we tackle the edit-distance problem-the problem of computing the most similar pair of strings in the two respective languages. In particular, we consider three different gap cost models for the edit-distance that are crucial for finding a proper alignment between two bio sequences: The linear, affine and concave models. We design efficient algorithms for the edit-distance between a CFG and an FA under these gap cost models. The time complexity of our algorithm for computing the linear or affine gap distance is polynomial and the time complexity for the concave gap distance is exponential.

Original language	English
Pages (from-to)	278-289
Number of pages	12
Journal	Information and Computation
Volume	247
DOIs	https://doi.org/10.1016/j.ic.2016.02.001
Publication status	Published - 2016 Apr 1

Bibliographical note

Funding Information:
Ko and Han were supported by the Basic Science Research Program through NRF funded by MEST ( 2015R1D1A1A01060097 ), the Yonsei University Future-leading Research Initiative of 2015 and the International Cooperation Program managed by NRF of Korea ( 2014K2A1A2048512 ), and Salomaa was supported by the Natural Sciences and Engineering Research Council of Canada Grant OGP0147224 .

Publisher Copyright:
© 2016 Elsevier Inc. All rights reserved.

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Information Systems
Computer Science Applications
Computational Theory and Mathematics

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10.1016/j.ic.2016.02.001

Cite this

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abstract = "For a given context-free grammar (CFG) and a finite-state automaton (FA), we tackle the edit-distance problem-the problem of computing the most similar pair of strings in the two respective languages. In particular, we consider three different gap cost models for the edit-distance that are crucial for finding a proper alignment between two bio sequences: The linear, affine and concave models. We design efficient algorithms for the edit-distance between a CFG and an FA under these gap cost models. The time complexity of our algorithm for computing the linear or affine gap distance is polynomial and the time complexity for the concave gap distance is exponential.",

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N2 - For a given context-free grammar (CFG) and a finite-state automaton (FA), we tackle the edit-distance problem-the problem of computing the most similar pair of strings in the two respective languages. In particular, we consider three different gap cost models for the edit-distance that are crucial for finding a proper alignment between two bio sequences: The linear, affine and concave models. We design efficient algorithms for the edit-distance between a CFG and an FA under these gap cost models. The time complexity of our algorithm for computing the linear or affine gap distance is polynomial and the time complexity for the concave gap distance is exponential.

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Approximate matching between a context-free grammar and a finite-state automaton

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

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