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