DocumentCode
2413431
Title
Improving Spatial Semantic Analysis by a Combining Model
Author
Li, Shiqi ; Zhao, Tiejun ; Li, Hanjing
Author_Institution
Sch. of Comput. Sci. & Technol., Harbin Inst. of Technol., Harbin, China
fYear
2010
fDate
7-9 May 2010
Firstpage
1430
Lastpage
1433
Abstract
This paper presents a combination base machine learning approach to spatial semantic analysis in Chinese. The model consists of multiple pre-training classifiers and a gating mechanism for integrating the outputs of these classifiers. Then we use EM algorithm to train the parameters of the combining model. Finally the experimental results show an overall improvement on the standard corpus CPB.
Keywords
information analysis; learning (artificial intelligence); natural language processing; pattern classification; Chinese language; EM algorithm; combination base machine learning; combining model; gating mechanism; multiple pretraining classifiers; spatial semantic analysis; Classification algorithms; Labeling; Niobium; Semantics; Support vector machine classification; Training; classifier combination; mixture of experts; spatial semantic analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
E-Business and E-Government (ICEE), 2010 International Conference on
Conference_Location
Guangzhou
Print_ISBN
978-0-7695-3997-3
Type
conf
DOI
10.1109/ICEE.2010.363
Filename
5591533
Link To Document