@inproceedings{kruengkrai-etal-2006-conditional,
title = "A Conditional Random Field Framework for {T}hai Morphological Analysis",
author = "Kruengkrai, Canasai and
Sornlertlamvanich, Virach and
Isahara, Hitoshi",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Gangemi, Aldo and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Tapias, Daniel",
booktitle = "Proceedings of the Fifth International Conference on Language Resources and Evaluation ({LREC}{'}06)",
month = may,
year = "2006",
address = "Genoa, Italy",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2006/pdf/137_pdf.pdf",
abstract = "This paper presents a framework for Thai morphological analysis based on the theoretical background of conditional random fields. We formulate morphological analysis of an unsegmented language as the sequential supervised learning problem. Given a sequence of characters, all possibilities of word/tag segmentation are generated, and then the optimal path is selected with some criterion. We examine two different techniques, including the Viterbi score and the confidence estimation. Preliminary results are given to show the feasibility of our proposed framework.",
}
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<abstract>This paper presents a framework for Thai morphological analysis based on the theoretical background of conditional random fields. We formulate morphological analysis of an unsegmented language as the sequential supervised learning problem. Given a sequence of characters, all possibilities of word/tag segmentation are generated, and then the optimal path is selected with some criterion. We examine two different techniques, including the Viterbi score and the confidence estimation. Preliminary results are given to show the feasibility of our proposed framework.</abstract>
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%0 Conference Proceedings
%T A Conditional Random Field Framework for Thai Morphological Analysis
%A Kruengkrai, Canasai
%A Sornlertlamvanich, Virach
%A Isahara, Hitoshi
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Gangemi, Aldo
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Tapias, Daniel
%S Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)
%D 2006
%8 May
%I European Language Resources Association (ELRA)
%C Genoa, Italy
%F kruengkrai-etal-2006-conditional
%X This paper presents a framework for Thai morphological analysis based on the theoretical background of conditional random fields. We formulate morphological analysis of an unsegmented language as the sequential supervised learning problem. Given a sequence of characters, all possibilities of word/tag segmentation are generated, and then the optimal path is selected with some criterion. We examine two different techniques, including the Viterbi score and the confidence estimation. Preliminary results are given to show the feasibility of our proposed framework.
%U http://www.lrec-conf.org/proceedings/lrec2006/pdf/137_pdf.pdf
Markdown (Informal)
[A Conditional Random Field Framework for Thai Morphological Analysis](http://www.lrec-conf.org/proceedings/lrec2006/pdf/137_pdf.pdf) (Kruengkrai et al., LREC 2006)
ACL