A Polynomial Algorithm for the Inference of Context Free Languages

Alexander Clark, Rémi Eyraud, Amaury Habrard

Research output: Chapter in Book/Report/Conference proceedingOther chapter contribution

25 Citations (Scopus)

Abstract

We present a polynomial algorithm for the inductive inference of a large class of context free languages, that includes all regular languages. The algorithm uses a representation which we call Binary Feature Grammars based on a set of features, capable of representing richly structured context free languages as well as some context sensitive languages. More precisely, we focus on a particular case of this representation where the features correspond to contexts appearing in the language. Using the paradigm of positive data and a membership oracle, we can establish that all context free languages that satisfy two constraints on the context distributions can be identified in the limit by this approach. The polynomial time algorithm we propose is based on a generalisation of distributional learning and uses the lattice of context occurrences. The formalism and the algorithm seem well suited to natural language and in particular to the modelling of first language acquisition.
Original languageEnglish
Title of host publicationGrammatical Inference: Algorithms and Applications
EditorsAlexander Clark, François Coste, Laurent Miclet
Place of PublicationBerlin
PublisherSpringer
Pages29-42
Number of pages14
Volume5278
ISBN (Electronic)978-3-540-88009-7
ISBN (Print)978-3-540-88008-0
DOIs
Publication statusPublished - 2008

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Berlin Heidelberg

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