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Unsupervised Information Extraction by Text Segmentation

Part of the book series: SpringerBriefs in Computer Science ((BRIEFSCOMPUTER))

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Abstract

The Information Extraction problem (IE) refers to the automatic extraction of structured information from noisy unstructured textual sources. This problem is a research topic in different Computer Science communities, such as: Databases, Information Retrieval, and Artificial Intelligence. This chapter provides an introduction of this problem and also an overview of how information extraction fits into the broader topics of data management. It also provides a list of the main contribution that can be found in this book.

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Authors and Affiliations

  1. Instituto de Computação, Universidade Federal do Amazonas, Manaus, AM, Brazil

    Eli Cortez & Altigran S. da Silva

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  1. Eli Cortez
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  2. Altigran S. da Silva
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Correspondence to Eli Cortez .

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Cortez, E., da Silva, A.S. (2013). Introduction. In: Unsupervised Information Extraction by Text Segmentation. SpringerBriefs in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-02597-1_1

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  • DOI: https://doi.org/10.1007/978-3-319-02597-1_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-02596-4

  • Online ISBN: 978-3-319-02597-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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