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Knowledge Reuse: Survey of Existing Techniques and Classification Approach

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Business Intelligence (eBISS 2014)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 205))

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Abstract

The importance of managing organizational knowledge for enterprises has been recognized since decades. The expectation is that systematic development and reuse of knowledge will help to improve the competitiveness of an enterprise. The paper investigates different approaches for knowledge reuse from computer science and business information systems. Starting from a description of different knowledge reuse perspectives and examples of knowledge reuse approaches from literature, the paper proposes a classification approach for knowledge reuse techniques. The criteria included in the approach are reuse technique, reuse situation, capacity of knowledge representation, addressee of knowledge, validation status, scope and phase of solution development. The main contributions of this paper is (1) a summary of the context for knowledge reuse from knowledge management and knowledge engineering (2) a set of criteria for comparing and categorizing knowledge reuse techniques derived from literature in the field, and (3) selected reuse techniques classified according to the criteria developed as initial validation of these classification scheme.

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Notes

  1. 1.

    Source: www.vocabulary.com. Last access: October 13, 2014.

  2. 2.

    http://ontologydesignpatterns.org.

  3. 3.

    EU-FP7 funded IP that ended in February 2010 - http://www.neon-project.org.

  4. 4.

    http://www.gong.manchester.ac.uk/odp/html/index.html.

  5. 5.

    http://ontologydesignpatterns.org/wiki/Submissions:Bag.

  6. 6.

    eBISS = 4th European Business Intelligence Summer School, Berlin, July 2014.

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Acknowledgement

We would like to thank the anonymous reviewers for their valuable comments which helped to improve the paper.

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Authors and Affiliations

  1. Institute of Computer Science, University of Rostock, 18051, Rostock, Germany

    Kurt Sandkuhl

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  1. Kurt Sandkuhl
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Correspondence to Kurt Sandkuhl .

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  1. Université Libre de Bruxelles, Brussels, Belgium

    Esteban Zimányi

  2. Technische Universtät Berlin, Berlin, Germany

    Ralf-Detlef Kutsche

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Sandkuhl, K. (2015). Knowledge Reuse: Survey of Existing Techniques and Classification Approach. In: Zimányi, E., Kutsche, RD. (eds) Business Intelligence. eBISS 2014. Lecture Notes in Business Information Processing, vol 205. Springer, Cham. https://doi.org/10.1007/978-3-319-17551-5_5

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  • DOI: https://doi.org/10.1007/978-3-319-17551-5_5

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-17550-8

  • Online ISBN: 978-3-319-17551-5

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