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Computation of distances for regular and context-free probabilistic languages

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Date
01/05/2008
Author
Nederhof, Mark Jan
Satta, Giorgio
Keywords
Probabilistic context-free languages
Probabilistic finite automata
Probabilistic language distances
Language entropy
Kullback-Leibler divergence
Relative entropy
Models
QA75 Electronic computers. Computer science
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Abstract
Several mathematical distances between probabilistic languages have been investigated in the literature, motivated by applications in language modeling, computational biology, syntactic pattern matching and machine learning. In most cases, only pairs of probabilistic regular languages were considered. In this paper we extend the previous results to pairs of languages generated by a probabilistic context-free grammar and a probabilistic finite automaton.
Citation
Nederhof , M J & Satta , G 2008 , ' Computation of distances for regular and context-free probabilistic languages ' , Theoretical Computer Science , vol. 395 , no. 2-3 , pp. 235-254 . https://doi.org/10.1016/j.tcs.2008.01.010
Publication
Theoretical Computer Science
Status
Peer reviewed
DOI
https://doi.org/10.1016/j.tcs.2008.01.010
ISSN
0304-3975
Type
Journal article
Rights
This is an author version of an article published in Theoretical Computer Science 395 (2008), available at http://www.sciencedirect.com
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  • University of St Andrews Research
URL
http://www.scopus.com/inward/record.url?scp=45849119469&partnerID=8YFLogxK
URI
http://hdl.handle.net/10023/1658

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