TY - GEN
T1 - Distributional learning of abstract categorial grammars
AU - Yoshinaka, Ryo
AU - Kanazawa, Makoto
N1 - Funding Information:
This work was supported in part by Mext Kakenshi 20700124 and by the NII joint research project “Open Problems on Multiple Context-Free Grammars”.
PY - 2011
Y1 - 2011
N2 - Recent studies on grammatical inference have demonstrated the benefits of the learning strategy called "distributional learning" for context-free and multiple context-free languages. This paper gives a comprehensive view of distributional learning of "context-free" formalisms (roughly in the sense of Courcelle 1987) in terms of abstract categorial grammars, in which existing "context-free" formalisms can be encoded.
AB - Recent studies on grammatical inference have demonstrated the benefits of the learning strategy called "distributional learning" for context-free and multiple context-free languages. This paper gives a comprehensive view of distributional learning of "context-free" formalisms (roughly in the sense of Courcelle 1987) in terms of abstract categorial grammars, in which existing "context-free" formalisms can be encoded.
UR - http://www.scopus.com/inward/record.url?scp=79960137741&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79960137741&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-22221-4_17
DO - 10.1007/978-3-642-22221-4_17
M3 - Conference contribution
AN - SCOPUS:79960137741
SN - 9783642222207
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 251
EP - 266
BT - Logical Aspects of Computational Linguistics - 6th International Conference, LACL 2011, Proceedings
T2 - 6th International Conference on Logical Aspects of Computational Linguistics, LACL 2011
Y2 - 29 June 2011 through 1 July 2011
ER -