Tagging for Intelligent Processing of Design Information

  • Hideaki Takeda
  • Yutaka Fujimoto
  • Masaharu Yoshioka
  • Yoshiki Shimomura
  • Kengo Morimoto
  • Wataru Oniki
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3609)

Abstract

This paper describes how to add tags to design documents in order to extract knowledge from information for intelligent design support. Our project called Universal Abduction Studio (UAS) aims to build a new design support system that supports conceptual design by dynamically integrating knowledge in different design domains. This paper focuses on knowledge description form which can be used to capture knowledge from text-based information and then be used for inference for creative design. We propose so-called design knowledge document containing both human-readable texts and machine-readable knowledge such as propositions and rules.

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References

  1. 1.
    Takeda, H., Sakai, H., Nomaguchi, Y., Yoshioka, M., Shimomura, Y., Tomiyama, T.: Universal abduction studio – proposal of a design support envrionment for creative thinking in design –. In: Folkman, A., Gralen, K., Norell, M., Sellgren, U. (eds.) The Fourteenth International Conference on Engineering Design (ICED 03), Stockholm (2003)Google Scholar
  2. 2.
    Takeda, H., Yoshioka, M., Tomiyama, T.: A general framework for modeling of synthesis – integration of theories of synthesis –. In: 13th International Conference on Engineering Design – ICED 01, Design Research – Theories, Methodologies, and Product Modelling, Glasgow, pp. 307–314 (2001)Google Scholar
  3. 3.
    Takeda, H., Tomiyama, T., Yoshikawa, H.: A Logical and Computerable framework for reasoning in design. In: Taylor, D., Stauffer, L. (eds.) Design Theory and Methodology, DTM ’92, pp. 167–174. The American Society of Mechanical Engineers (ASME), New York (1992)Google Scholar
  4. 4.
    Takeda, H., Veerkamp, P., Tomiyama, T., Yoshikawa, H.: Modeling design processes. AI Magazine 11(4), 37–48 (1990)Google Scholar
  5. 5.
    Hayashi, K., Takeda, H., Tomiyama, T., Yoshikawa, H.: Analysis and logical formalization of design processes (the third report) – modeling with circumscription and abduction – (In Japanese). In: The proceedings of the annual conference of the Japanese Society for Precision Engineering, pp. 7–8 (1989)Google Scholar
  6. 6.
    Coyne, R.: Logic Models of Design. Pitman Publishing, London (1988)MATHGoogle Scholar
  7. 7.
    Roozenburg, N., Eekels, J.: Product Design: Fundamentals and Methods. John Wiley & Sons, Chichester (1995)Google Scholar
  8. 8.
    Peirce, C.: Collected Papers of Charles Sanders Peirce, vol. 5. Harvard University Press, Cambridge (1935)Google Scholar
  9. 9.
    Flach, P., Kakas, A. (eds.): Abductive and Inductive Reasoning: Essays on their Relation and Integration. Kluwer Academic Publishers, Dordrecht (2000)Google Scholar
  10. 10.
    Schurz, G.: Models of abductive reasoning. In: Schurz, G., Werning, M. (eds.): TPD Preprints Annual. Number 1 in Philosophical Prepublication Series of the Chair of Theoretical Philosophy. The University of Dusseldorf (2002)Google Scholar
  11. 11.
    Aliseda, A.: Abduction as epistemic change: A peircean model in artificial intelligence. In: Flach, P., Kakas, A. (eds.) Abductive and Inductive Reasoning: Essays on their Relation and Integration. Applied Logic Series, Kluwer Academic Publishers, Dordrecht (2000)Google Scholar
  12. 12.
    Takeda, H.: Abduction for design. In: Gero, J., Sudweeks, F. (eds.) Proceedings of the IFIP WG5.2 International Workshop on Formal Design Method for CAD, Tallinn, Elsevier Science Publishers B.V., Amsterdam (1993)Google Scholar
  13. 13.
    Tomiyama, T.: From general design theory to knowledge-intensive engineering. Artificial Intelligence for Engineering Design, Analysis and Manufacturing (AIEDAM) 8, 319–333 (1994)CrossRefGoogle Scholar
  14. 14.
    Gruber, T.R.: Toward principles for the design of ontologies used for knowledge sharing. Technical Report KSL 93-4, Knowledge Systems Laboratory, Stanford University (1993)Google Scholar
  15. 15.
    Yoshioka, M., Umeda, Y., Takeda, H., Shimomura, Y., Nomaguchi, Y., Tomiyama, T.: Physical concept ontology for the knowledge intensive engineering framework (Advanced Engineering Informatics) (Accepted for publication)Google Scholar
  16. 16.
    Watanabe, H.: Hits for mechanical design, A second series (In Japanese). Nikkan Kogyo Shinbun, Tokyo (1998)Google Scholar
  17. 17.
    Yoshioka, M., Shamoto, Y.: Knowledge Management System for Problem Solving – Integration of Document Information and Formalized Knowledge –. In: Proceedings of the 2003 ASME Design Engineering Technical Conference & Computers and Information in Engineering Conference, The American Society of Mechanical Engineers (ASME), New York, DETC2003/CIE-48217 (CD-ROM) (2003)Google Scholar
  18. 18.
    Berners-Lee, T., Hendler, J., Lassila, O.: The semantic web. Scientific American (2001)Google Scholar

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Hideaki Takeda
    • 1
  • Yutaka Fujimoto
    • 2
  • Masaharu Yoshioka
    • 3
  • Yoshiki Shimomura
    • 2
  • Kengo Morimoto
    • 2
  • Wataru Oniki
    • 2
  1. 1.National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430Japan
  2. 2.Research into Artifacts, Center for Engineering (RACE), The University of Tokyo, Komaba 4-6-1, Meguro-ku, Tokyo 153-8904Japan
  3. 3.Graduate School of Information Science and Technology, Hokkaido University, Kita 14 Nishi 9, Kita-ku, Sapporo, Hokkaido, 060-0814Japan

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