Reference metadata extraction using a hierarchical knowledge representation framework

Authors:
Min-Yuh Day;Richard Tzong-Han Tsai;Cheng-Lung Sung;Chiu-Chen Hsieh;Cheng-Wei Lee;Shih-Hung Wu;Kun-Pin Wu;Chorng-Shyong Ong;Wen-Lian Hsu
Affiliations:
Institute of Information Science, Academia Sinica, Nankang, Taipei 115, Taiwan, ROC and Department of Information Management, National Taiwan University, Taipei 106, Taiwan, ROC;Institute of Information Science, Academia Sinica, Nankang, Taipei 115, Taiwan, ROC;Institute of Information Science, Academia Sinica, Nankang, Taipei 115, Taiwan, ROC;Institute of Information Science, Academia Sinica, Nankang, Taipei 115, Taiwan, ROC;Institute of Information Science, Academia Sinica, Nankang, Taipei 115, Taiwan, ROC;Department of CSIE, Chaoyang University of Technology, Taichung County 413, Taiwan, ROC;Institute of Information Science, Academia Sinica, Nankang, Taipei 115, Taiwan, ROC;Department of Information Management, National Taiwan University, Taipei 106, Taiwan, ROC;Institute of Information Science, Academia Sinica, Nankang, Taipei 115, Taiwan, ROC
Venue:
Decision Support Systems
Year:
2007

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Abstract

The integration of bibliographical information on scholarly publications available on the Internet is an important task in the academic community. Accurate reference metadata extraction from such publications is essential for the integration of metadata from heterogeneous reference sources. In this paper, we propose a hierarchical template-based reference metadata extraction method for scholarly publications. We adopt a hierarchical knowledge representation framework called INFOMAP, which automatically extracts metadata. The experimental results show that, by using INFOMAP, we can extract author, title, journal, volume, number (issue), year, and page information from different kinds of reference styles with a high degree of precision. The overall average accuracy is 92.39% for the six major reference styles compared in this study.