期刊名称：International Journal on Electrical Engineering and Informatics
印刷版ISSN：2085-6830
出版年度：2010
卷号：2
期号：4
出版社：School of Electrical Engineering and Informatics
摘要：The rapid growth of Internet causes the abundance of textual information. It is necessary to have smart tools and methods than can access text content as needed. One of the success methods is Support Vector Machine (SVM). This paper will discuss how the performance of the SVM-GATE algorithm on extracting information from Indonesian language corpus in response toτmargin variation. Experimental results show that there is optimumτmargin for both Indonesian corpus of Vegetable Market and Seminar Announcement Corpus. The best Performance of SVM-GATE obtained at the τMargin of 0.5 and the Window Size of 4x4.
关键词：Information Extraction; Support Vector Machine; Bahasa Indonesia Corpus; NLP;GATE; optimum margin.
