DocumentCode :
532247
Title :
Efficiently identifying semantic orientation algorithm for Chinese words
Author :
Han, Hongming ; Mo, Qian ; Zuo, Min ; Duan, Dagao
Author_Institution :
Sch. of Comput. Sci. & Inf. Eng., Beijing Technol. & Bus. Univ., Beijing, China
Volume :
2
fYear :
2010
fDate :
22-24 Oct. 2010
Abstract :
In this paper, two methods for effective semantic orientation identification algorithm are proposed, which are based on HowNet. Some criteria for computing the orientation similarity between given word and benchmark words set are compared and a k-NN classification for determining semantic orientation for given word is proposed. Comprehensive experiments are conducted and the result show the k-NN method can effectively identify common words semantic orientation and accuracy rate has greatly been improved arriving at 96.5%.
Keywords :
natural language processing; pattern classification; Chinese words; HowNet; k-NN classification method; semantic orientation identification algorithm; Dispersion; Semantics; k-NN classification; opinion mining; semantic orientation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
Type :
conf
DOI :
10.1109/ICCASM.2010.5620207
Filename :
5620207
Link To Document :
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