Improving Information Extraction using Knowledge Model

被引：0
|
作者：
Chen, Yue [1 ]
机构：
[1] Beijing Inst Technol, Sch Comp Sci & Technol, 5 Zhongguancun Nandajie Haidian Dist, Beijing 100081, Peoples R China
来源：
PROCEEDINGS OF THE 24TH PACIFIC ASIA CONFERENCE ON LANGUAGE, INFORMATION AND COMPUTATION | 2010年
关键词：
Natural Language Processing; Information Extraction; knowledge model; knowledge representation;
D O I：
暂无
中图分类号：
H0 [语言学];
学科分类号：
030303 ; 0501 ; 050102 ;
摘要：
This paper describes the work on automated Information Extraction that accepts arbitrary text and extracts information from the text. A new approach to implement Information Extraction system is proposed in this paper. Firstly, the article will be decomposed according to paragraph, sentence and phrase. Every sentence will be compared with the knowledge node, and then append the information extracted to the knowledge model. Finally, the answers are generated to the questions about the input text. With the experimental corpus the accuracy rate of knowledge matching is 63.5%, and accuracy rate of question answering is 65.0% with the system knowledge model.
引用
收藏
页码：613 / 620
页数：8
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