Abstract
Portable Document Format (PDF) is increasingly being recognized as a common format of electronic documents. The prerequisite to management and indexing of PDF files is to extract information from them. This paper describes an approach for extracting information from PDF files. The key idea is to transform the text information parsed from PDF files into semi-structured information by injecting additional uniform tags. An extensible rule set is built on tags and other knowledge. Guided by the rules, one pattern matching algorithm based on a tree model is applied to obtain the necessary information. A further experiment proved that this method was effective.
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References
Muslea, I., Minton, S., Knoblock, C.A.: Hierarchical approach to wrapper induction. In: Proceedings of the Third International Conference on Autonomous Agents, Seattle, WA 1999, pp. 221–227 (1999)
Kushmerick, N.: Wrapper Induction: Efficiency and expressiveness. Artificial Intelligence (118), 15–68 (2000)
Zhu, M., Wang, J., Wang, J.: Multiple Record Extraction from HTML Page Based On Hierarchical Pattern. Computer Engineering 27(9), 40–42 (2001)
Zhu, M., Huang, Y., Cai, Q.: Information Extraction From Web Pages Based on Multi-Knowledge. Mini-Micro System 22(9), 1058–1061 (2001)
Adobe Systems Incorporated. Adobe Portable Document Format Version 1.4, American Addison Wesley (2001)
Ben Litchfield PDFBOX[CP], http://sourceforge.net/projects/pdfbox/
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© 2006 Springer-Verlag Berlin Heidelberg
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Yuan, F., Liu, B., Yu, G. (2006). A Study on Information Extraction from PDF Files. In: Yeung, D.S., Liu, ZQ., Wang, XZ., Yan, H. (eds) Advances in Machine Learning and Cybernetics. Lecture Notes in Computer Science(), vol 3930. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11739685_27
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DOI: https://doi.org/10.1007/11739685_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33584-9
Online ISBN: 978-3-540-33585-6
eBook Packages: Computer ScienceComputer Science (R0)