Emerging Novel Scenarios of New Product Design with Teamwork on Scenario Maps Using Pictorial KeyGraph

  • Kenichi Horie
  • Yukio Ohsawa
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4253)


We developed a method of teamwork for products design in real manufacturing company, where Scenario Maps using Pictorial KeyGraph assist creating novel scenarios of new product design. In Pictorial KeyGraph, photographs of physical objects corresponding to incomprehensible items in given data are embedded to the visual result of KeyGraph applied to their business report. In their communications with Pictorial KeyGraph, novel and practical scenarios of new products design were extracted, and 5 new patents have been applied. We found evidences that the team members tend to combine established concepts via rare words in creative designing.


Product Design Chance Discovery Test Report Real Entity Black Node 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Ohsawa, Y.: Modeling the Process of Chance Discovery. In: Ohsawa, Y., McBurney, P. (eds.) Chance Discovery, pp. 2–15. Springer, Heidelberg (2003)Google Scholar
  2. Ohsawa, Y., McBurney, P. (eds.): Chance discovery (Advanced information processing). Springer, Heidelberg (2003)Google Scholar
  3. Ohsawa, Y., Benson, E.N., Yachida, M.: KeyGraph: Automatic Indexing by Co-occurrence Graph based on Building Construction Metaphor. In: Proc. Advanced Digital Library Conference (IEEE ADL 1998), pp. 2–18 (1998)Google Scholar
  4. Kushiro, N., Ohsawa: A Scenario Acquisition Method with Multi-Dimensional Hearing and Hierarchical Accommodation Process. New Mathematics and Natural Computation 1(4) (2006)Google Scholar
  5. Gaver, W.W., et al.: Ambiguity as a Resource for Design. In: Proceedings of Computer Human Interactions (2003)Google Scholar
  6. Ohsawa, Y.: Chance Discovery for Making Decisions in Complex Real World. New Generation Computing 20(2), 143–163 (2002)MATHCrossRefGoogle Scholar
  7. Ohsawa, Y., Nara, Y.: Decision process modeling across Internet and real world by double helical model of chance discovery. New generation computing 21, 109–121 (2003)MATHCrossRefGoogle Scholar
  8. Okazaki, N., Ohsawa, Y.: Polaris: An Integrated Data Miner for Chance Discovery. In: Proceedings of The Third International Workshop on Chance Discovery and Its Management, Crete, Greece (2003)Google Scholar
  9. Goldberg, D.E.: The Design of Innovation: Lessons from and for Competent Genetic Algorithms. Kluwer Academic Publishers, Boston (2002)MATHGoogle Scholar
  10. Eris, O.: Effective Inquiry for Innovative Engineering Design. Kluwer Academic Publishers, Dordrecht (2004)CrossRefGoogle Scholar
  11. Fruchter, R., et al.: Knowledge reuse through chance discovery from an enterprise design-build enterprise data store. New Mathematics and Natural Computation 3, 393–406 (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Kenichi Horie
    • 1
  • Yukio Ohsawa
    • 1
  1. 1.Department of Quantum Engineering and Systems Science, Graduate School of EngineeringThe University of TokyoTokyoJapan

Personalised recommendations