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
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;
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
DOI :
10.1109/ICCASM.2010.5620207