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Statistical Analysis of Bibliographic Strings for Constructing an Integrated Document Space

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Research and Advanced Technology for Digital Libraries (ECDL 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2458))

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Abstract

It is important to utilize retrospective documents when constructing a large digital library. This paper proposes a method for analyzing recognized bibliographic strings using an extended hidden Markov model. The proposed method enables analysis of erroneous bibliographic strings and integrates many documents accumulated as printed articles in a citation index. The proposed method has the advantage of providing a robust bibliographic matching function using the statistical description of the syntax of bibliographic strings, a language model and an Optical Character Recognition (OCR) error model. The method also has the advantage of reducing the cost of preparing training data for parameter estimation, using records in the bibliographic database.

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Author information

Authors and Affiliations

  1. National Institute of Informatics, 2-1-2 Hitotsubashi, 101-8430, Chiyoda-ku Tokyo, Japan

    Atsuhiro Takasu

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  1. Atsuhiro Takasu
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Editor information

Editors and Affiliations

  1. Department of Information Engineering, University of Padua, Via Gradenigo 6/a, 35131, Padova, Italy

    Maristella Agosti

  2. Istituto di Scienza e Tecnologie dell’ Informazione (ISTI-CNR), Area della Ricerca CNR di Pisa, Via G. Moruzzi 1, 56124, Pisa, Italy

    Costantino Thanos

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© 2002 Springer-Verlag Berlin Heidelberg

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Takasu, A. (2002). Statistical Analysis of Bibliographic Strings for Constructing an Integrated Document Space. In: Agosti, M., Thanos, C. (eds) Research and Advanced Technology for Digital Libraries. ECDL 2002. Lecture Notes in Computer Science, vol 2458. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45747-X_6

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  • DOI: https://doi.org/10.1007/3-540-45747-X_6

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44178-6

  • Online ISBN: 978-3-540-45747-3

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