Title :
A Two-Layer SVM Classification Mechanism for Chinese Blog Article
Author :
Luo, Guo-Heng ; Liu, Jia-chiam ; Yuan, Shyan-Ming
Author_Institution :
Inst. of Comput. Sci. & Eng., Nat. Chiao-Tung Univ., Hsinchu, Taiwan
Abstract :
In Taiwan, the famous bloggers can be regard as professional writers now. More and more people subscribe their RSS (Really Simple Syndication) to receive updated information. But readers might only interest in few categories of articles, readers need to filter other articles by themselves. In order to help people select the information they want, this research proposed a two-layer SVM classification mechanism to classify blog articles. The schema is also evaluated in this research and the experiment result the proposed schema achieves 87% of recall and 95% of precision.
Keywords :
Web sites; classification; support vector machines; Chinese blog article; RSS; SVM; Taiwan; classification mechanism; really simple syndication; Blogs; Dictionaries; Filtering; Support vector machine classification; Text categorization; Training; Article Classification; Blog; Data Mining; Machine Learning;
Conference_Titel :
Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), 2011 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4577-1827-4
DOI :
10.1109/CyberC.2011.12