Abstract
With the recent proliferation of documents, automatic metadata extraction from document becomes an important task. In this paper, we propose a novel template matching based method for header metadata extraction form semi-structured documents stored in PDF. In our approach, templates are defined, and the document is considered as strings with format. Templates are used to guide finite state automaton (FSA) to extract header metadata of papers. The testing results indicate that our approach can effectively extract metadata, without any training cost and available to some special situation. This approach can effectively assist the automatic index creation in lots of fields such as digital libraries, information retrieval, and data mining.
This paper is supported by the National 973 Key Basic Research Program under grant No.2003CB317003, and the Cultivation Fund of the Key Scientific and Technical Innovation Project, Ministry of Education of China under grant No.705034.
An erratum to this chapter can be found at http://dx.doi.org/10.1007/11915072_109.
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Huang, Z., Jin, H., Yuan, P., Han, Z. (2006). Header Metadata Extraction from Semi-structured Documents Using Template Matching. In: Meersman, R., Tari, Z., Herrero, P. (eds) On the Move to Meaningful Internet Systems 2006: OTM 2006 Workshops. OTM 2006. Lecture Notes in Computer Science, vol 4278. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11915072_84
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DOI: https://doi.org/10.1007/11915072_84
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