Header Metadata Extraction from Semi-structured Documents Using Template Matching

  • Zewu Huang
  • Hai Jin
  • Pingpeng Yuan
  • Zongfen Han
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4278)


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.


Data Stream Digital Library Template Match Finite State Automaton Layout Information 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Zewu Huang
    • 1
  • Hai Jin
    • 1
  • Pingpeng Yuan
    • 1
  • Zongfen Han
    • 1
  1. 1.Cluster and Grid Computing LabHuazhong University of Science and TechnologyWuhanChina

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