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SciPlore Xtract: Extracting Titles from Scientific PDF Documents by Analyzing Style Information (Font Size)

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Part of the Lecture Notes in Computer Science book series (LNISA,volume 6273)

Abstract

Extracting titles from a PDF’s full text is an important task in information retrieval to identify PDFs. Existing approaches apply complicated and expensive (in terms of calculating power) machine learning algorithms such as Support Vector Machines and Conditional Random Fields. In this paper we present a simple rule based heuristic, which considers style information (font size) to identify a PDF’s title. In a first experiment we show that this heuristic delivers better results (77.9% accuracy) than a support vector machine by CiteSeer (69.4% accuracy) in an ‘academic search engine’ scenario and better run times (8:19 minutes vs. 57:26 minutes).

Keywords

  • header extraction
  • title extraction
  • style information
  • document analysis

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  • DOI: 10.1007/978-3-642-15464-5_45
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References

  1. Han, H., Giles, C.L., Manavoglu, E., Zha, H., Zhang, Z., Fox, E.A.: Automatic document metadata extraction using support vector machines. In: Proceedings of the 3rd ACM/IEEE-CS Joint Conference on Digital libraries, pp. 37–48 (2003)

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  2. Hu, Y., Li, H., Cao, Y., Teng, L., Meyerzon, D., Zheng, Q.: Automatic extraction of titles from general documents using machine learning. Information Processing and Management 42(5), 1276–1293 (2006)

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  3. Peng, F., McCallum, A.: Accurate Information extraction from research papers using conditional random fields. Information Processing and Management 42(4), 963–979 (2006)

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© 2010 Springer-Verlag Berlin Heidelberg

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Beel, J., Gipp, B., Shaker, A., Friedrich, N. (2010). SciPlore Xtract: Extracting Titles from Scientific PDF Documents by Analyzing Style Information (Font Size). In: Lalmas, M., Jose, J., Rauber, A., Sebastiani, F., Frommholz, I. (eds) Research and Advanced Technology for Digital Libraries. ECDL 2010. Lecture Notes in Computer Science, vol 6273. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15464-5_45

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  • DOI: https://doi.org/10.1007/978-3-642-15464-5_45

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15463-8

  • Online ISBN: 978-3-642-15464-5

  • eBook Packages: Computer ScienceComputer Science (R0)