Title
An Information Extraction Method for Digitized Textbooks of Traditional Chinese Medicine
Abstract
Digital libraries have shouldered the mission of preserving and spreading human culture in the era of information. However, knowledge extraction for digital libraries is not well studied, and that holds back the role promotion of digital libraries from information collector to knowledge provider. This paper presents an ontology-based approach, which extracts detailed attributes of Traditional Chinese Medicine (TCM) from digitized textbooks. According to the characters of digitized textbooks, we propose an extraction ontology that is compatible with both textbook extraction and TCM theory. To improve extraction tolerance for OCR errors, we extract features of different aspects. Finally, a structured pattern based extraction method is adopted to minimize extraction supervision. The result shows that our method is a practical and robust exploration to address the problem of information extraction for digitized textbooks of TCM.
Year
DOI
Venue
2010
10.1109/CIT.2010.291
CIT
Keywords
Field
DocType
knowledge provider,extraction method,traditional chinese medicine,ocr errors,information extraction,information extraction method,digital library,human culture,extraction ontology,textbook extraction,digital libraries,pattern based extraction,extraction tolerance,features extract,feature extraction,extraction supervision,ontologies (artificial intelligence),optical character recognition,data mining,tcm theory,knowledge extraction,digitized textbook,text analysis,information collector,digitized textbooks,support vector machines,ontologies
Ontology (information science),Ontology,Information retrieval,Computer science,Support vector machine,Optical character recognition,Feature extraction,Information extraction,Knowledge extraction,Digital library
Conference
ISBN
Citations 
PageRank 
978-1-4244-7547-6
1
0.40
References 
Authors
4
5
Name
Order
Citations
PageRank
Wenhao Zhu11510.99
Shunlai Bai220.75
Bofeng Zhang317941.38
Weimin Xu4617.98
Daming Wei521544.97