Title
Learning regular tree languages from correction and equivalence queries
Abstract
Inspired by the results obtained in the string case, we present in this paper the extension of the correction queries to regular tree languages. Relying on Angluin's and Sakakibara's work, we introduce the algorithm LRTLC and we show that regular tree languages are learnable from equivalence and correction queries when the set of contexts is ordered by a Knuth-Bendix order. Moreover, a subclass of regular tree languages, called injective languages, is learned without equivalence queries. This can be extended for other subclasses and may have some practical relevance in fields like machine translation, pattern and speech recognition, building XML documents.
Year
Venue
Keywords
2007
Journal of Automata, Languages and Combinatorics
correction query,speech recognition,regular tree language,injective language,algorithm lrtlc,knuth-bendix order,machine translation,xml document,equivalence query,practical relevance
Field
DocType
Volume
Generalized star height problem,Discrete mathematics,Query language,Formal language,Regular tree grammar,Machine translation,Abstract family of languages,Theoretical computer science,Equivalence (measure theory),Cone (formal languages),Mathematics
Journal
12
Issue
Citations 
PageRank 
4
4
0.41
References 
Authors
8
2
Name
Order
Citations
PageRank
Catalin Ionut Tîrnauca192.58
Cristina Tîrnauca2123.26