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Intelligent Information Systems for Knowledge Work(ers)

  • Klaus-Dieter Althoff
  • Björn Decker
  • Alexandre Hanft
  • Jens Mänz
  • Régis Newo
  • Markus Nick
  • Jörg Rech
  • Martin Schaaf
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4065)

Abstract

Our society needs and expects more high-value services. Such “knowledge-intensive” services can only be delivered if the necessary organizational and technical requirements are fulfilled. In addition, the cost-benefit analysis from the service provider point of view needs to be positive. Continuous improvement and goal-directed (partial) automation of such services is therefore of crucial importance. As a contribution to this we describe our current research vision for (partially) automated support of knowledge work(ers) based on intelligent information systems focusing on the use of experience. For the implementation of such a vision we base on the integration of approaches from artificial intelligence and software engineering. A “deep” integration of case-based reasoning and experience factory is a first successful step in this direction [33, 28]. We envision the further integration of software product-lines and multi-agent systems as the next one.

Keywords

Experience Factory Multiagent System Software Agent Software Product Line Knowledge Work 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Aha, D.W.: The AAAI-99 KM/CBR Workshop: Summary of Contributions. In: Proc. ICCBR 1999 Workshops, pp. II-37–II-44. Technical Report, LSA-99-03E, TU Kaiserslautern (1999)Google Scholar
  2. 2.
    Althoff, K.-D., Mänz, J., Nick, M.: Maintaining Experience to Learn: Case Studies on Case-Based Reasoning and Experience Factory. In: Proc. 6th Workshop Days of the German Computer Science Society (GI) on Learning, Knowledge, and Adaptivity (LWA 2005) Workshop on Machine Learning, Knowledge Discovery, and Data Mining, Saarland University, Germany (October 2005)Google Scholar
  3. 3.
    Althoff, K.-D.: Case-Based Reasoning. In: Chang, S.K. (ed.) Handbook on Software Engineering and Knowledge Engineering, vol. 1, pp. 549–587. World Scientific, Singapore (2001)CrossRefGoogle Scholar
  4. 4.
    Althoff, K.-D., Kockskämper, S., Maurer, F., Stadler, M., Wess, S.: Ein System zur fallbasierten Wissensverarbeitung in technischen Diagnosesituationen. In: Retti, J., Leidlmeier, K. (eds.) 5th Austrian AI-Conference, pp. 65–70. Springer, Heidelberg (1989)Google Scholar
  5. 5.
    Althoff, K.-D., Auriol, E., Barletta, R., Manago, M.: A Review of Industrial Case-Based Reasoning Tools. AI Perspectives Report. AI Intelligence, Oxford (1995)Google Scholar
  6. 6.
    Althoff, K.-D., Nick, M.: How to Support Experience Management with Evaluation - Foundations, Evaluation Methods, and Examples for Case-Based Reasoning and Experience Factory, LNCS(LNAI). Springer, Heidelberg (accepted for publication) (in progress)Google Scholar
  7. 7.
    Aamodt, A., Plaza, E.: Case-based reasoning: Foundational issues, methodological variations, and system approaches. AI Communications 7(1), 39–59 (1994)Google Scholar
  8. 8.
    Bartsch-Spörl, B.: Ansätze zur Behandlung von fallorientiertem Erfahrungswissen in Expertensystemen. KI 4, 32–36 (1987)Google Scholar
  9. 9.
    Basili, V.R., Caldiera, G., Rombach, H.D.: Experience Factory. In: Mar-ciniak, J.J. (ed.) Encyclopedia of SE, vol. 1, pp. 469–476. John Wiley & Sons, Chichester (1994)Google Scholar
  10. 10.
    Basili, V.R., Caldiera, G., Rombach, H.D.: Goal Question Metric Paradigm. In: Marciniak, J.J. (ed.) Encyclopedia of SE, vol. 1, pp. 528–532. Wiley & Sons, Chichester (1994)Google Scholar
  11. 11.
    Basili, V.R., Caldiera, G., McGarry, F., et al.: The Software Engineering Laboratory-An Operational Software Experience Factory. In: Proceedings of the Fourteenth International Conference on Software Engineering (ICSE 1992), 12 pages (May 1992)Google Scholar
  12. 12.
    Basili, V.R.: Quantitative evaluation of software methodology. In: Proceedings of the First Pan-Pacific Computer Conference, Melbourne, Australia (September 1985)Google Scholar
  13. 13.
    Bergmann, R., Althoff, K.-D., Breen, S., Göker, M.H., Manago, M., Traphöner, R., Wess, S. (eds.): Developing Industrial Case-Based Reasoning Applications. LNCS (LNAI), vol. 1612. Springer, Heidelberg (2003)Google Scholar
  14. 14.
    Bullinger, H.-J., Ilg, R.: Leben und Arbeiten in einer vernetzten, mobilen Welt. In: Uhr, W., Esswein, W., Schoop, E. (Hrsg.). Wirtschaftsinformatik 2003 Band I, pp. 1–8. Physica Verlag (2003)Google Scholar
  15. 15.
    Bibel, W., Andler, D., Da Costa, O., Küppers, G., Pearson, I.D.: Converging Technologies and the Natural, Social and Cultural World. Report of the EU High Level Expert Group on Forsighting the New Technology Wave (FoNTWave) (June 30, 2004)Google Scholar
  16. 16.
    Basili, V.R., Rombach, H.D.: The TAME Project: Towards improvement-oriented software environments. IEEE Transactions on SE SE-14(6), 758–773 (1988)CrossRefGoogle Scholar
  17. 17.
    Burkhard, H.-D.: Software-Agenten. In: Görz, G., Rollinger, C.-R., Schneeberger, J. (eds.) Handbuch der Künstlichen Intelligenz, Auflage, vol. 4, pp. 943–1020.Google Scholar
  18. 18.
    Cramer, J.: Management wissensintensiver Dienstleistungen. In: [Her03a], pp. 179–203Google Scholar
  19. 19.
    Brasse, C., Uhlmann, M.: Integration von Erfahrungswissen. In: [Her03a], pp. 121–132Google Scholar
  20. 20.
    Decker, B., Althoff, K.-D.: Prozesslernen und Erfahrungsmanagement: Ergebnisse aus dem indiGo-Projekt. In: Proc. Lernen - Wissen - Adaptivität 2004 (LWA 2004), pp. 138–145 (2004)Google Scholar
  21. 21.
    Ducatel, K., Bogdanowicz, M., Scapolo, F., Lejten, J., Burgelman, J.-C.: Scenarios of Ambient Intelligence in 2010. IST Advisory Group (ISTAG), European Commission Community Research (2001)Google Scholar
  22. 22.
    Hermann, S. (Hrsg.): Integrierter Schlussbericht - Verbundprojekt SIAM Strategien, Instrumente und arbeitsorganisatorische Gestaltungsmodelle zur Förderung der Dienstleistungskompetenz in Unternehmen, 2003 (accessed, October 20, 2005), http://www.siam.iao.fraunhofer.de/intern/intern-berichte/siam-schlussbericht-final.doc
  23. 23.
    Hermann, S.: Produktive Wissensarbeit - Eine Herausforderung. In: [Her03a], pp. 204–224Google Scholar
  24. 24.
    Kiehl, M.: Arbeitsmarktentwicklung und wissensintensive Dienstleistungen im östlichen Ruhrgebiet. Universität Dortmund, LS VWL, insb. Raumwirtschaftspolitik, Arbeitskreis Strukturpolitik (June 12, 2003)Google Scholar
  25. 25.
    Bundesministerium für Forschung und Technologie, Bekanntmachung über die Förderung von Forschungsvorhaben auf dem Gebiet Wissensintensive Dienstleistungen (January 14, 2000)Google Scholar
  26. 26.
    Kolodner, J.L.: Case-Based Reasoning. Morgan Kaufmann Publishers, San Mateo (1993)Google Scholar
  27. 27.
    Muthig, D.: Systematischer Aufbau und Einsatz von Wissen zur effizienten Entwicklung von Software-Varianten. KI (2), 5–11 (2005)Google Scholar
  28. 28.
    Nick, M.: Experience Maintenance through Closed-Loop Feedback. Ph.D Thesis, Department of Computer Science, University of Kaiserslautern (2005)Google Scholar
  29. 29.
    Rech, J., Althoff, K.-D.: Artificial Intelligence and Software Engineering - Status and Future Trends. Special Issue on Artificial Intelligence & Software Engineering, KI (3), 5–11 (2004)Google Scholar
  30. 30.
    Schmid, K.: Systematische Wiederverwendung im Produktlinienumfeld - Ein Enscheidungsproblem. Special Issue on Artificial Intelligence & Software Engineering, KI (3), 33–35 (2004)Google Scholar
  31. 31.
    Schmid, K.: Planning Software Reuse - A Disciplined Scoping Approach for Software Product Lines. Ph.D thesis, University of Kaiserslautern. IRB Verlag (2002)Google Scholar
  32. 32.
    Schank, R.C.: Dynamic Memory: A Theory of Learning in Computers and People. Cambridge University Press, Cambridge (1982)Google Scholar
  33. 33.
    Tautz, C.: Customizing Software Engineering Experience Management Systems to Organizational Needs. Ph.D Thesis, Department of Computer Science, University of Kaiserslautern, Fraunhofer IRB Verlag (2000)Google Scholar
  34. 34.
    Watson, I. (ed.): Applying Knowledge Management: techniques for building corporate memories. Morgan Kaufmann Publishers Inc., San Francisco (2003)Google Scholar
  35. 35.
    Wei, G. (ed.): Multiagent systems. A modern approach to distributed artificial intelligence. The MIT Press, Cambridge (1999)Google Scholar
  36. 36.
    Willke, H.: Organisierte Wissensarbeit. In: Zeitschrift für Soziologie, vol. 3, pp. 161–177 (1998)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Klaus-Dieter Althoff
    • 1
  • Björn Decker
    • 2
  • Alexandre Hanft
    • 1
  • Jens Mänz
    • 1
  • Régis Newo
    • 1
  • Markus Nick
    • 2
  • Jörg Rech
    • 2
  • Martin Schaaf
    • 1
  1. 1.Institute of Computer Sciences, Laboratory of Intelligent Information SystemsUniversity of Hildesheim 
  2. 2.Department for Experience ManagementFraunhofer Institute for Experimental Software EngineeringKaiserslautern

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