Integration of the dual approaches in the distributional learning of context-free grammars

Ryo Yoshinaka

doi:10.1007/978-3-642-28332-1_46

Integration of the dual approaches in the distributional learning of context-free grammars

Ryo Yoshinaka

INF - System Information Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

13 Citations (Scopus)

Abstract

Recently several "distributional learning algorithms" have been proposed and have made great success in learning different subclasses of context-free grammars. The distributional learning models and exploits the relation between strings and contexts that form grammatical sentences in the language of the learning target. There are two main approaches. One, which we call primal, constructs nonterminals whose language is supposed to be characterized by strings. The other, which we call dual, uses contexts to characterize the language of each nonterminal of the conjecture grammar. This paper shows how those opposite approaches are integrated into single learning algorithms that learn quite rich classes of context-free grammars.

Original language	English
Title of host publication	Language and Automata Theory and Applications - 6th International Conference, LATA 2012, Proceedings
Pages	538-550
Number of pages	13
DOIs	https://doi.org/10.1007/978-3-642-28332-1_46
Publication status	Published - 2012
Event	6th International Conference on Language and Automata Theory and Applications, LATA 2012 - A Coruna, Spain Duration: 2012 Mar 5 → 2012 Mar 9

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7183 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	6th International Conference on Language and Automata Theory and Applications, LATA 2012
Country/Territory	Spain
City	A Coruna
Period	12/3/5 → 12/3/9

Access to Document

10.1007/978-3-642-28332-1_46

Cite this

Yoshinaka, R. (2012). Integration of the dual approaches in the distributional learning of context-free grammars. In Language and Automata Theory and Applications - 6th International Conference, LATA 2012, Proceedings (pp. 538-550). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7183 LNCS). https://doi.org/10.1007/978-3-642-28332-1_46

@inproceedings{cd4c3193cdc14e4f8949edabff65c2b0,

title = "Integration of the dual approaches in the distributional learning of context-free grammars",

abstract = "Recently several {"}distributional learning algorithms{"} have been proposed and have made great success in learning different subclasses of context-free grammars. The distributional learning models and exploits the relation between strings and contexts that form grammatical sentences in the language of the learning target. There are two main approaches. One, which we call primal, constructs nonterminals whose language is supposed to be characterized by strings. The other, which we call dual, uses contexts to characterize the language of each nonterminal of the conjecture grammar. This paper shows how those opposite approaches are integrated into single learning algorithms that learn quite rich classes of context-free grammars.",

author = "Ryo Yoshinaka",

year = "2012",

doi = "10.1007/978-3-642-28332-1_46",

language = "English",

isbn = "9783642283314",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "538--550",

booktitle = "Language and Automata Theory and Applications - 6th International Conference, LATA 2012, Proceedings",

note = "6th International Conference on Language and Automata Theory and Applications, LATA 2012 ; Conference date: 05-03-2012 Through 09-03-2012",

}

Yoshinaka, R 2012, Integration of the dual approaches in the distributional learning of context-free grammars. in Language and Automata Theory and Applications - 6th International Conference, LATA 2012, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7183 LNCS, pp. 538-550, 6th International Conference on Language and Automata Theory and Applications, LATA 2012, A Coruna, Spain, 12/3/5. https://doi.org/10.1007/978-3-642-28332-1_46

Integration of the dual approaches in the distributional learning of context-free grammars. / Yoshinaka, Ryo.
Language and Automata Theory and Applications - 6th International Conference, LATA 2012, Proceedings. 2012. p. 538-550 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7183 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Integration of the dual approaches in the distributional learning of context-free grammars

AU - Yoshinaka, Ryo

PY - 2012

Y1 - 2012

N2 - Recently several "distributional learning algorithms" have been proposed and have made great success in learning different subclasses of context-free grammars. The distributional learning models and exploits the relation between strings and contexts that form grammatical sentences in the language of the learning target. There are two main approaches. One, which we call primal, constructs nonterminals whose language is supposed to be characterized by strings. The other, which we call dual, uses contexts to characterize the language of each nonterminal of the conjecture grammar. This paper shows how those opposite approaches are integrated into single learning algorithms that learn quite rich classes of context-free grammars.

AB - Recently several "distributional learning algorithms" have been proposed and have made great success in learning different subclasses of context-free grammars. The distributional learning models and exploits the relation between strings and contexts that form grammatical sentences in the language of the learning target. There are two main approaches. One, which we call primal, constructs nonterminals whose language is supposed to be characterized by strings. The other, which we call dual, uses contexts to characterize the language of each nonterminal of the conjecture grammar. This paper shows how those opposite approaches are integrated into single learning algorithms that learn quite rich classes of context-free grammars.

UR - http://www.scopus.com/inward/record.url?scp=84857853456&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84857853456&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-28332-1_46

DO - 10.1007/978-3-642-28332-1_46

M3 - Conference contribution

AN - SCOPUS:84857853456

SN - 9783642283314

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 538

EP - 550

BT - Language and Automata Theory and Applications - 6th International Conference, LATA 2012, Proceedings

T2 - 6th International Conference on Language and Automata Theory and Applications, LATA 2012

Y2 - 5 March 2012 through 9 March 2012

ER -

Yoshinaka R. Integration of the dual approaches in the distributional learning of context-free grammars. In Language and Automata Theory and Applications - 6th International Conference, LATA 2012, Proceedings. 2012. p. 538-550. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-28332-1_46

Integration of the dual approaches in the distributional learning of context-free grammars

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this