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Automated Processing of Digitized Historical Newspapers: Identification of Segments and Genres

  • Conference paper
Digital Libraries: Universal and Ubiquitous Access to Information (ICADL 2008)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5362))

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Abstract

Many historical newspapers are being digitized. We aim to support access to them via text analysis of the OCRd content. However, the OCR includes many errors; so extracting meaningful content from it is difficult. A pipeline of processing steps is proposed. Here, we describe the first two steps: segmentation and genre identification. The segmentation procedure based on headings was quite successful. Genre identification worked well for easily defined genre categories such as weather reports. We also propose additional techniques which may improve the accuracy still farther.

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References

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Author information

Authors and Affiliations

  1. College of Information Science and Technology, Drexel University, USA

    Robert B. Allen, Ilya Waldstein & Weizhong Zhu

Authors
  1. Robert B. Allen
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  2. Ilya Waldstein
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  3. Weizhong Zhu
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Swansea University, Singleton Park, SA2 8PP, Swansea, UK

    George Buchanan

  2. Computer Science Department, The University of Waikato, Hamilton, New Zealand

    Masood Masoodian

  3. Computer Science Department, University of Waikato, Hamilton, New Zealand

    Sally Jo Cunningham

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© 2008 Springer-Verlag Berlin Heidelberg

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Allen, R.B., Waldstein, I., Zhu, W. (2008). Automated Processing of Digitized Historical Newspapers: Identification of Segments and Genres. In: Buchanan, G., Masoodian, M., Cunningham, S.J. (eds) Digital Libraries: Universal and Ubiquitous Access to Information. ICADL 2008. Lecture Notes in Computer Science, vol 5362. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89533-6_49

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  • DOI: https://doi.org/10.1007/978-3-540-89533-6_49

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89532-9

  • Online ISBN: 978-3-540-89533-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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