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Introduction to Text Analytics

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Big Data Management and Analytics (eBISS 2019)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 390))

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Abstract

Data processing regards analysis of various types of data, including numerical data, signals, texts, pictures, videos, etc. This paper focuses on defining and studying various tasks of text analytics following the typical processing pipeline. Sources of textual data are introduced and related challenges are discussed. Along with the process of text analytics, examples are presented to demonstrate how text analytics should be carried out. Finally, potential applications of text analytics are given including sentiment analysis and automatic generation of content.

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Notes

  1. 1.

    https://en.wikipedia.org/wiki/Text_mining.

  2. 2.

    https://en.wikipedia.org/wiki/Parsing.

  3. 3.

    https://en.wikipedia.org/wiki/Regular_expression.

  4. 4.

    https://en.wikipedia.org/wiki/XPath.

  5. 5.

    http://openrefine.org/download.html.

  6. 6.

    https://medium.com/@sumn2u/cosine-similarity-between-two-sentences-8f6630b0ebb7.

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Author information

Authors and Affiliations

  1. Department of Information Systems, Poznan University of Economics and Business, Poznan, Poland

    Agata Filipowska & Dominik Filipiak

Authors
  1. Agata Filipowska
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  2. Dominik Filipiak
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Corresponding author

Correspondence to Agata Filipowska .

Editor information

Editors and Affiliations

  1. Technische Universtät Berlin, Berlin, Germany

    Ralf-Detlef Kutsche

  2. Université Libre de Bruxelles, Brussels, Belgium

    Esteban Zimányi

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Filipowska, A., Filipiak, D. (2020). Introduction to Text Analytics. In: Kutsche, RD., Zimányi, E. (eds) Big Data Management and Analytics. eBISS 2019. Lecture Notes in Business Information Processing, vol 390. Springer, Cham. https://doi.org/10.1007/978-3-030-61627-4_2

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  • DOI: https://doi.org/10.1007/978-3-030-61627-4_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-61626-7

  • Online ISBN: 978-3-030-61627-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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