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Answering with Cases: A CBR Approach to Deep Learning

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Case-Based Reasoning Research and Development (ICCBR 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11156))

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Abstract

Every year tenths of thousands of customer support engineers around the world deal with, and proactively solve, complex help-desk tickets. Daily, almost every customer support expert will turn his/her attention to a prioritization strategy, to achieve the best possible result. To assist with this, in this paper we describe a novel case-based reasoning application to address the tasks of: high solution accuracy and shorter prediction resolution time. We describe how appropriate cases can be generated to assist engineers and how our solution can scale over time to produce domain-specific reusable cases for similar problems. Our work is evaluated using data from 5000 cases from the automotive industry.

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Author information

Authors and Affiliations

  1. German Research Center for Artificial Intelligence, Smart Data and Knowledge Services, Trippstadter Strae 122, 67663, Kaiserslautern, Germany

    Kareem Amin, Klaus-Dieter Althoff & Andreas Dengel

  2. Institute of Computer Science, Intelligent Information Systems Lab, University of Hildesheim, Hildesheim, Germany

    Klaus-Dieter Althoff

  3. Kaiserslautern University, P.O. Box 3049, 67663, Kaiserslautern, Germany

    Kareem Amin & Andreas Dengel

  4. School of Computing Engineering and Mathematics, University of Brighton, Brighton, UK

    Stelios Kapetanakis

  5. Gluru Research, Gluru, London, UK

    Stelios Kapetanakis

  6. Department of Computing, University of Middlesex, London, UK

    Miltos Petridis

Authors
  1. Kareem Amin
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  2. Stelios Kapetanakis
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  3. Klaus-Dieter Althoff
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  4. Andreas Dengel
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  5. Miltos Petridis
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Corresponding author

Correspondence to Kareem Amin .

Editor information

Editors and Affiliations

  1. Wright State University, Dayton, OH, USA

    Michael T. Cox

  2. Mälardalen University, Västeras, Sweden

    Peter Funk

  3. Mälardalen University, Västeras, Sweden

    Shahina Begum

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Amin, K., Kapetanakis, S., Althoff, KD., Dengel, A., Petridis, M. (2018). Answering with Cases: A CBR Approach to Deep Learning. In: Cox, M., Funk, P., Begum, S. (eds) Case-Based Reasoning Research and Development. ICCBR 2018. Lecture Notes in Computer Science(), vol 11156. Springer, Cham. https://doi.org/10.1007/978-3-030-01081-2_2

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  • DOI: https://doi.org/10.1007/978-3-030-01081-2_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01080-5

  • Online ISBN: 978-3-030-01081-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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