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Semi-automatic Knowledge Extraction from Semi-structured and Unstructured Data Within the OMAHA Project

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Case-Based Reasoning Research and Development (ICCBR 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9343))

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Abstract

This paper describes a workflow for semi-automatic knowledge extraction for case-based diagnosis in the aircraft domain. There are different types of data sources: structured, semi-structured and unstructured source. Because of the high number of data sources available and necessary, a semi-automatic extraction and transformation of the knowledge is required to support the knowledge engineers. This support shall be performed by a part of our multi-agent system for aircraft diagnosis. First we describe our multi-agent system to show the context of the knowledge extraction. Then we describe our idea of the workflow with its single tasks and substeps. At last the current implementation, and evaluation of our system is described.

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Notes

  1. 1.

    Completion rules derive attribute values with a certainty factor if the respective condition is fulfilled (a set of attribute values).

  2. 2.

    A relevance matrix describes the relevance of available attributes concerning available diagnoses (e.g., [9]).

  3. 3.

    Assuming, here and the further occurrences, that the similarity measures can take values from the [0;1] interval.

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Author information

Authors and Affiliations

  1. German Research Center for Artificial Intelligence, Kaiserslautern, Germany

    Pascal Reuss & Klaus-Dieter Althoff

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

    Pascal Reuss & Klaus-Dieter Althoff

  3. Airbus, Kreetslag 10, 21129, Hamburg, Germany

    Wolfram Henkel & Matthias Pfeiffer

  4. Lufthansa Industry Solutions, Norderstedt, Germany

    Oliver Hankel & Roland Pick

Authors
  1. Pascal Reuss
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  2. Klaus-Dieter Althoff
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  3. Wolfram Henkel
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  4. Matthias Pfeiffer
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  5. Oliver Hankel
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  6. Roland Pick
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Corresponding author

Correspondence to Pascal Reuss .

Editor information

Editors and Affiliations

  1. Universität Paderborn, Paderborn, Germany

    Eyke Hüllermeier

  2. Goethe-Universität Frankfurt, Frankfurt/Main, Germany

    Mirjam Minor

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Reuss, P., Althoff, KD., Henkel, W., Pfeiffer, M., Hankel, O., Pick, R. (2015). Semi-automatic Knowledge Extraction from Semi-structured and Unstructured Data Within the OMAHA Project. In: Hüllermeier, E., Minor, M. (eds) Case-Based Reasoning Research and Development. ICCBR 2015. Lecture Notes in Computer Science(), vol 9343. Springer, Cham. https://doi.org/10.1007/978-3-319-24586-7_23

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  • DOI: https://doi.org/10.1007/978-3-319-24586-7_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24585-0

  • Online ISBN: 978-3-319-24586-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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