DocumentCode
2486068
Title
Word Segmentation Using Domain Knowledge Based on Conditional Random Fields
Author
Fukuda, Takuya ; Izumi, Masataka ; Miura, Takao
Author_Institution
Hosei Univ., Tokyo
Volume
2
fYear
2007
fDate
29-31 Oct. 2007
Firstpage
436
Lastpage
439
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
learning (artificial intelligence); natural language processing; probability; random processes; text analysis; Japanese word segmentation; conditional random field; domain knowledge; domain specific feature function; probabilistic parameter; text processing; training data; Artificial intelligence; Dictionaries; Natural languages; Pattern analysis; Speech; Statistics; Stochastic processes; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Tools with Artificial Intelligence, 2007. ICTAI 2007. 19th IEEE International Conference on
Conference_Location
Patras
ISSN
1082-3409
Print_ISBN
978-0-7695-3015-4
Type
conf
DOI
10.1109/ICTAI.2007.93
Filename
4410418
Link To Document