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A Controlled Natural Language for Business Intelligence Monitoring

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Natural Language Processing and Information Systems (NLDB 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9103))

Abstract

With ever increasing information available in social networks, the number of businesses attempting to exploit it is on the rise, particularly by keeping track of their customers’ posts and likes on social media sites like Facebook. Whilst APIs can be used to automate the tracking process, writing scripts to extract information and process it requires considerable technical skill and is thus not an option for non technical business analysts. On the other hand, off-the-shelf business intelligence solutions do not provide the desired flexibility for the specific needs of particular businesses. In this paper, we present a controlled natural language enabling non-technical users to express their queries in a language they can easily understand but which can be directly compiled into executable code.

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Notes

  1. 1.

    Check-ins are events when users register their presence at a particular location or business premises.

  2. 2.

    http://sourceforge.net/projects/chatscript for question detection and http://sentiment.vivekn.com for sentiment analysis.

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Author information

Authors and Affiliations

  1. University of Malta, Msida, Malta

    Christian Colombo, Jean-Paul Grech & Gordon J. Pace

Authors
  1. Christian Colombo
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  2. Jean-Paul Grech
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  3. Gordon J. Pace
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Corresponding authors

Correspondence to Christian Colombo or Gordon J. Pace .

Editor information

Editors and Affiliations

  1. Technische Universität Darmstadt, Darmstadt, Germany

    Chris Biemann

  2. Universität Passau, Passau, Germany

    Siegfried Handschuh

  3. Universität Passau, Passau, Germany

    André Freitas

  4. University of Salford, Salford, United Kingdom

    Farid Meziane

  5. Conservatoire National des Arts et Métiers, Paris, France

    Elisabeth Métais

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Colombo, C., Grech, JP., Pace, G.J. (2015). A Controlled Natural Language for Business Intelligence Monitoring. In: Biemann, C., Handschuh, S., Freitas, A., Meziane, F., Métais, E. (eds) Natural Language Processing and Information Systems. NLDB 2015. Lecture Notes in Computer Science(), vol 9103. Springer, Cham. https://doi.org/10.1007/978-3-319-19581-0_27

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  • DOI: https://doi.org/10.1007/978-3-319-19581-0_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19580-3

  • Online ISBN: 978-3-319-19581-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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