A Rule-based Framework of Metadata Extraction from Scientific Papers

被引：2
|
作者：
Guo, Zhixin [1 ]
Jin, Hai [1 ]
机构：
[1] Huazhong Univ Sci & Technol, Serv Comp Technol & Syst Lab, Cluster & Grid Comp Lab, Wuhan 430074, Peoples R China
来源：
2011 TENTH INTERNATIONAL SYMPOSIUM ON DISTRIBUTED COMPUTING AND APPLICATIONS TO BUSINESS, ENGINEERING AND SCIENCE (DCABES) | 2011年
关键词：
document metadata; information extraction; rule-based approach;
D O I：
10.1109/DCABES.2011.14
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Most scientific documents on the web are unstructured or semi-structured, and the automatic document metadata extraction process becomes an important task. This paper describes a framework for automatic metadata extraction from scientific papers. Based on a spatial and visual knowledge principle, our system can extract title, authors and abstract from scientific papers. We utilize format information such as font size and position to guide the metadata extraction process. The experiment results show that our system achieves a high accuracy in header metadata extraction which can effectively assist the automatic index creation for digital libraries.
引用
收藏
页码：400 / 404
页数：5
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