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Document Layout Analysis for Semantic Information Extraction

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AI*IA 2017 Advances in Artificial Intelligence (AI*IA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10640))

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Abstract

Using machines to automatically extract relevant information from unstructured and semi-structured sources has practical significance in todays life and business. In this context, although understanding the meaning of words is important, the process of identifying self-consistent geometric and logical regions of interest—blocks, cells, columns and tables, as well as paragraphs, titles and captions, only to mention a few—is of paramount importance too. This complex process goes under the name of document layout analysis. In this work, we discuss newly designed techniques to solve this problem effectively, by combining both syntactic and semantic document aspects. These techniques described here are at the basis of KnowRex, a comprehensive system for ontology-driven Information Extraction.

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Authors and Affiliations

  1. Department of Mathematics and Computer Science, University of Calabria, 87036, Rende, Italy

    Weronika T. Adrian, Nicola Leone, Marco Manna & Cinzia Marte

  2. AGH University of Science and Technology, Krakow, Poland

    Weronika T. Adrian

Authors
  1. Weronika T. Adrian
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  2. Nicola Leone
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  3. Marco Manna
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  4. Cinzia Marte
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Corresponding author

Correspondence to Weronika T. Adrian .

Editor information

Editors and Affiliations

  1. University of Bari, Bari, Italy

    Floriana Esposito

  2. University of Rome Tor Vergata, Rome, Italy

    Roberto Basili

  3. University of Bari, Bari, Italy

    Stefano Ferilli

  4. University of Bari, Bari, Italy

    Francesca A. Lisi

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Adrian, W.T., Leone, N., Manna, M., Marte, C. (2017). Document Layout Analysis for Semantic Information Extraction. In: Esposito, F., Basili, R., Ferilli, S., Lisi, F. (eds) AI*IA 2017 Advances in Artificial Intelligence. AI*IA 2017. Lecture Notes in Computer Science(), vol 10640. Springer, Cham. https://doi.org/10.1007/978-3-319-70169-1_20

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  • DOI: https://doi.org/10.1007/978-3-319-70169-1_20

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  • Print ISBN: 978-3-319-70168-4

  • Online ISBN: 978-3-319-70169-1

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