DocumentCode :
3429355
Title :
Domain Dependent Word Segmentation Based on Conditional Random Fields
Author :
Fukuda, Takuya ; Izumi, Masataka ; Miura, Takao
Author_Institution :
Univ. of Hosei, Tokyo
fYear :
2007
fDate :
22-24 Aug. 2007
Firstpage :
268
Lastpage :
271
Abstract :
In this investigation, we propose an experimental approach for word segmentation in Japanese under domain-dependent situation. We apply Conditional Random Fields (CRF) to our issue. CRF learns several probabilistic parameters from training data with specific feature functions dependent on domains. Here we propose how to define domain specific feature functions.
Keywords :
character recognition; probability; Japanese; conditional random fields; domain dependent word segmentation; probabilistic parameters; training data; Airports; Dictionaries; Hidden Markov models; Natural languages; Pattern analysis; Speech; Statistics; Stochastic processes; Tagging; Training data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications, Computers and Signal Processing, 2007. PacRim 2007. IEEE Pacific Rim Conference on
Conference_Location :
Victoria, BC
Print_ISBN :
978-1-4244-1189-4
Electronic_ISBN :
1-4244-1190-4
Type :
conf
DOI :
10.1109/PACRIM.2007.4313226
Filename :
4313226
Link To Document :
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