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Biblio: automatic meta-data extraction

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Abstract

Biblio is an adaptive system that automatically extracts meta-data from semi-structured and structured scanned documents. Instead of using hand-coded templates or other methods manually customized for each given document format, it uses example-based machine learning to adapt to customer-defined document and meta-data types. We provide results from experiments on the recognition of document information in two document corpuses: a set of scanned journal articles and a set of scanned legal documents. The first set is semi-structured, as the different journals use a variety of flexible layouts. The second set is largely free-form text based on poor quality scans of FAX-quality legal documents. We demonstrate accuracy on the semi-structured document set roughly comparable to hand-coded systems, and much worse performance on the legal documents.

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Authors and Affiliations

  1. Hewlett-Packard Laboratories, Technion City, Haifa, 32000, Israel

    Carl Staelin & Marie Vans

  2. Hewlett-Packard Laboratories, Filton Road, Bristol, Stoke Gifford, BS34 8QZ, UK

    Darryl Greig

  3. The Computer Science Department, Israel Institute of Technology, 516 Taub building, Haifa, 32000, Israel

    Michael Elad & Oded Shmueli

Authors
  1. Carl Staelin
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  2. Michael Elad
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  3. Darryl Greig
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  4. Oded Shmueli
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  5. Marie Vans
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Correspondence to Carl Staelin.

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Staelin, C., Elad, M., Greig, D. et al. Biblio: automatic meta-data extraction. IJDAR 10, 113–126 (2007). https://doi.org/10.1007/s10032-006-0032-y

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