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2018 | OriginalPaper | Buchkapitel

Knowledge Engineering for Distributed Case-Based Reasoning Systems

verfasst von : Kerstin Bach

Erschienen in: Synergies Between Knowledge Engineering and Software Engineering

Verlag: Springer International Publishing

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Abstract

This chapter describes how to identify and collect human knowledge and transform it into machine readable and actionable knowledge. We will focus on the knowledge acquisition for distributed case-based reasoning systems. Case-based reasoning (CBR) is a well-known methodology for implementing knowledge-intensive decision support systems (Aamodt, Plaza, Artif Intell Commun, 7(1):39–59, 1994) [1] and has been applied in a broad range of applications. It captures experiences in the form of problem and solution pairs, which are recalled when similar problems reoccur. In order to create a CBR system the initial knowledge has to be identified and captured. In this chapter, we will summarise the knowledge acquisition method presented by Bach, Knowledge acquisition for case-based reasoning systems. Ph.D. thesis, University of Hildesheim, München (2012) [2] and give an running example within the travel medicine domain utilising the open source tool for developing CBR systems, myCBR.

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Vorheriges Kapitel Using the Event-B Formal Method and the Rodin Framework for Verification the Knowledge Base of an Rule-Based Expert System

Nächstes Kapitel Agile Knowledge Engineering for Mission Critical Software Requirements

http://dbpedia.org/.

https://developers.google.com/knowledge-graph/.

In the remaining parts of this work we will differentiate between snippet descriptions and snippet. Snippet descriptions are the conceptual representation of knowledge and are equivalent to a case representation. Snippets on the other hand are instances of snippet descriptions and therewith equivalent to cases.

http://www.bpmn.org/.

https://spring.io/.

Aamodt, A., Plaza, E.: Case-based reasoning: foundational issues, methodological variations, and system approaches. Artif. Intell. Commun. 7(1), 39–59 (1994)

Bach, K.: Knowledge acquisition for case-based reasoning systems. Ph.D. thesis, University of Hildesheim, München (2012). ISBN 978-3-8439-1357

Althoff, K.D., Reichle, M., Bach, K., Hanft, A., Newo, R.: Agent based maintenance for modularised case bases in collaborative multi-expert systems. In: Proceedings of AI2007, 12th UK Workshop on Case-Based Reasoning, pp. 7–18 (2007)

Reichle, M., Bach, K., Althoff, K.D.: Knowledge Engineering within the Application Independent Architecture SEASALT. In: Baumeister, J., Nalepa, G.J. (eds.) International Journal of Knowledge Engineering and Data Mining, pp. 202–215. Inderscience Publishers (2011)

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Bergmann, R., Althoff, K.D., Breen, S., Göker, M.H., Manago, M., Traphöner, R., Wess, S.: Selected applications of the structural case-based reasoning approach. Developing Industrial Case-Based Reasoning Applications: The INRECA-Methodology, LNCS, vol. 1612, pp. 35–70. Springer (2003)

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Bach, K., Reuss, P., Althoff, K.D.: Case-based menu creation as an example of individualized experience management. In: Maier, R., Kohlegger, M. (eds.) Professional Knowledge Management. Conference on Professional Knowledge Management (WM-2011), From Knowledge to Action, pp. 194–203. LNI 182, Köllen Druck & Verlag GmbH, Bonn (2011)

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Marter, S.: Case-Based Coordination Agents - Knowledge Modularization and Knowledge Composition (Fallbasierte Koordinationsagenten – Wissensmodularisierung und Wissenskomposition für dezentrale, heterogene Fallbasen). Master’s thesis, Institute of Computer Science, University of Hildesheim (2011)

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Bach, K., Althoff, K.D., Newo, R., Stahl, A.: A case-based reasoning approach for providing machine diagnosis from service reports. In: Ram, A., Wiratunga, N. (eds.) Proceedings of the 19th Intl. Conference on Case-Based Reasoning (ICCBR-2011), London, UK, LNCS, vol. 6880, pp. 363–377. Springer, Heidelberg (2011)

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Stahl, A., Roth-Berghofer, T.R.: Rapid prototyping of cbr applications with the open source tool mycbr. In: ECCBR ’08: Proceedings of the 9th European conference on Advances in Case-Based Reasoning, pp. 615–629. Springer, Berlin, Heidelberg (2008)

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Reuss, P.: Concept and Implementation of Knowledge Line Retrieval Strategies for Modularized, Homogeneous Topic Agents within a Multi-Agent-System (Konzept und Implementierung einer Knowledge line – Retrievalstrategien für modularisierte, homogene Topicagenten innerhalb eines Multi-Agenten-Systems). Hildesheim: Stiftung Universität Hildesheim, Institut für Informatik, Bereich Intelligente Informationssysteme, Master thesis (2012)

Titel: Knowledge Engineering for Distributed Case-Based Reasoning Systems
verfasst von: Kerstin Bach
Verlag: Springer International Publishing
Buch: Synergies Between Knowledge Engineering and Software Engineering
Print ISBN: 978-3-319-64160-7

Electronic ISBN: 978-3-319-64161-4

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-64161-4_7

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