Skip to main content
SpringerLink
Log in
Book cover

International Conference on Case-Based Reasoning

ICCBR 2017: Case-Based Reasoning Research and Development pp 302–314Cite as

Dependency Modeling for Knowledge Maintenance in Distributed CBR Systems

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10339))

Abstract

Knowledge-intensive software systems have to be continuously maintained to avoid inconsistent or false knowledge and preserve the problem solving competence, efficiency, and effectiveness. The more knowledge a system contains, the more dependencies between the different knowledge items may exist. Especially for an overall system, where several CBR systems are used as knowledge sources, several dependencies exist between the knowledge containers of the CBR systems. The dependencies have to be considered when maintaining the CBR systems to avoid inconsistencies between the knowledge containers. This paper gives an overview and formal definition of these maintenance dependencies. In addition, a first version of an algorithm to identify these dependencies automatically is presented. Furthermore, we describe the current implementation of dependency modeling in the open source tool myCBR.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. A Domain-Specific Language for Dependency Management in Model-Based Systems Engineering (2013)

    Google Scholar 

  2. Aamodt, A.: Modeling the knowledge contents of CBR systems. In: Proceedings of the Workshop Program at the Fourth International Conference on Case-Based Reasoning, pp. 32–37 (2001)

    Google Scholar 

  3. Al-Natour, S., Cavusoglu, H.: The strategic knowledge-based dependency diagrams: A tool for analyzing strategic knowledge dependencies for the purposes of understanding and communicating. Inf. Technol. Manage. 10(2–3), 103–121 (2009)

    Article  Google Scholar 

  4. Bach, K.: Knowledge Acquisition for Case-Based Reasoning Systems. Ph.D. thesis, University of Hildesheim , dr. Hut Verlag Muenchen 2013 (2012)

    Google Scholar 

  5. Bach, K., Sauer, C., Althoff, K.D., Roth-Berghofer, T.: Knowledge modeling with the open source tool myCBR. In: Nalepa, G.J., Baumeister, J., Kaczor, K. (eds.) Proceedings of the 10th Workshop on Knowledge Engineering and Software Engineering (KESE 2010). Workshop on Knowledge Engineering and Software Engineering (KESE-2014), located at 21st European Conference on Artificial Intelligence, August 19, Prague, Czech Republic. CEUR Workshop Proceedings (2014). http://ceur-ws.org/

  6. Davenport, T.H., Prusak, L.: Working Knowledge: How Organizations Manage What they Know. Havard Business School Press, Boston (2000)

    Google Scholar 

  7. Du, J., Bormann, J.: Improved similarity measure in case-based reasoning with global sensitivity analysis: an example of construction quantity estimating. J. Comput. Civ. Eng. 28(6), 04014020 (2012)

    Article  Google Scholar 

  8. Ferrario, M.A., Smyth, B.: Distributing case-based maintenance: The collaborative maintenance approach. Comput. Intell. 17(2), 315–330 (2001)

    Article  Google Scholar 

  9. Nick, M.: Experience Maintenance Loop through Closed-Loop Feedback. Ph.D. thesis, TU, Kaiserslautern (2005)

    Google Scholar 

  10. Patterson, D., Anand, S., Hughes, J.: A knowledge light approach to similarity maintenance for improving case-base competence. In: ECAI Workshop Notes, pp. 65–78 (2000)

    Google Scholar 

  11. Reuss, P., Althoff, K.D.: Explanation-aware maintenance of distributed case-based reasoning systems. In: Workshop Proceedings of the LWA 2013, Learning, Knowledge, Adaptation, pp. 231–325 (2013)

    Google Scholar 

  12. Reuss, P., Althoff, K.: Maintenance of distributed case-based reasoning systems in a multi-agent system. In: Proceedings of the 16th LWA Workshops: KDML, IR and FGWM, Aachen, Germany, 8–10 September 2014, pp. 20–30 (2014)

    Google Scholar 

  13. Reuss, P., Althoff, K.: Dependencies between knowledge for the case factory maintenance approach. In: Proceedings of the LWA 2015 Workshops: KDML, FGWM, IR, and FGDB, Trier, Germany, 7–9 October 2015, pp. 256–263 (2015)

    Google Scholar 

  14. Richter, M.M.: The knowledge contained in similarity measure. In: Invited Talk at the First International Conference on Case-Based Reasoning, ICCBR 1995 (1995)

    Google Scholar 

  15. Richter, M.M.: Fallbasiertes Schlieen. In: Handbuch der künstlichen Intelligenz, pp. 407–430. Oldenbourg Wissenschaftsverlag (2003)

    Google Scholar 

  16. Roth-Berghofer, T.: Knowledge Maintenance of Case-based Reasoning Systems: The SIAM Methodology. Akademische Verlagsgesellschaft Aka GmbH, Berlin (2003)

    Google Scholar 

  17. Sangal, N., Jordan, E., Sinha, V., Jackson, D.: Using dependency models to manage complex software architecture. In: Proceedings of the 20th Annual ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications, OOPSLA 2005, pp. 167–176. ACM, New York (2005)

    Google Scholar 

  18. Sell, C., Winkler, M., Springer, T., Schill, A.: Two dependency modeling approaches for business process adaptation. In: Karagiannis, D., Jin, Z. (eds.) KSEM 2009. LNCS (LNAI), vol. 5914, pp. 418–429. Springer, Heidelberg (2009). doi:10.1007/978-3-642-10488-6_40

    Chapter  Google Scholar 

  19. Smyth, B., Keane, M.: Remembering to forget: A competence-preserving case deletion policy for case-based reasoning systems. In: Proceedings of the 13th International Joint Conference on Artificial Intelligence, pp. 377–382 (1995)

    Google Scholar 

  20. Stahl, A.: Learning feature weights from case order feedback. In: Aha, D.W., Watson, I. (eds.) ICCBR 2001. LNCS, vol. 2080, pp. 502–516. Springer, Heidelberg (2001). doi:10.1007/3-540-44593-5_35

    Chapter  Google Scholar 

  21. Stahl, A., Roth-Berghofer, T.R.: Rapid prototyping of CBR applications with the open source tool myCBR. In: Althoff, K.-D., Bergmann, R., Minor, M., Hanft, A. (eds.) ECCBR 2008. LNCS, vol. 5239, pp. 615–629. Springer, Heidelberg (2008). doi:10.1007/978-3-540-85502-6_42

    Chapter  Google Scholar 

  22. Stram, R., Reuss, P., Althoff, K.-D., Henkel, W., Fischer, D.: Relevance matrix generation using sensitivity analysis in a case-based reasoning environment. In: Goel, A., Díaz-Agudo, M.B., Roth-Berghofer, T. (eds.) ICCBR 2016. LNCS, vol. 9969, pp. 402–412. Springer, Cham (2016). doi:10.1007/978-3-319-47096-2_27

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Intelligent Information Systems Lab, University of Hildesheim, Hildesheim, Germany

    Pascal Reuss, Christian Witzke & Klaus-Dieter Althoff

  2. Competence Center CBR, German Center for Artificial Intelligence, Kaiserslautern, Germany

    Pascal Reuss & Klaus-Dieter Althoff

Authors
  1. Pascal Reuss
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Christian Witzke
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Klaus-Dieter Althoff
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Pascal Reuss .

Editor information

Editors and Affiliations

  1. Naval Research Laboratory, Navy Center for Applied Research in AI, Washington, District of Columbia, USA

    David W. Aha

  2. LORIA/Bâtiment B/équipe Orpailleur, University of Lorraine, Vandœuvre-lès-Nancy Cedex, France

    Jean Lieber

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Reuss, P., Witzke, C., Althoff, KD. (2017). Dependency Modeling for Knowledge Maintenance in Distributed CBR Systems. In: Aha, D., Lieber, J. (eds) Case-Based Reasoning Research and Development. ICCBR 2017. Lecture Notes in Computer Science(), vol 10339. Springer, Cham. https://doi.org/10.1007/978-3-319-61030-6_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-61030-6_21

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61029-0

  • Online ISBN: 978-3-319-61030-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation