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A Rule-Based Framework of Metadata Extraction from Scientific Papers

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2 Author(s)
Zhixin Guo ; Cluster & Grid Comput. Lab., Huazhong Univ. of Sci. & Technol., Wuhan, China ; Hai Jin

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.

Published in:

Distributed Computing and Applications to Business, Engineering and Science (DCABES), 2011 Tenth International Symposium on

Date of Conference:

14-17 Oct. 2011

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