Design Entity Recognition for Bio-inspired Design Supervised State of the Art

  • Davide Russo
  • Pierre-Emmanuel FayemiEmail author
  • Matteo Spreafico
  • Giacomo Bersano
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 541)


In the last years the efforts spent for the enhancement of parsing engines led to several software more performant, in terms of both effectiveness in identification of syntax modules and speed of elaboration of the text, than the previous generation ones. Exploiting the benefits coming from such a new generation of software, nowadays the patent search can overcome the limits due to the classic FOS approach and performs it in a quasi-real-time way. This paper focuses on technical-problems identification methods based on syntactic dependency patterns, for ameliorating supervised state of the art and patent intelligence. Through parsing the patent text, very precise lists of technical problems are automatically extracted without the user being an expert in the problems of the sector. An exemplary case dealing with bio-inspired design is proposed, stressing what types of engineering problems are nowadays benefitting the most from the approach.


Biomimetics Biomimicry software Triz Syntactic parser 


  1. 1.
    Sartori, J., Pal, U., Chakrabarti, A.: A methodology for supporting transfer in biomimetic design. Artif. Intell. Eng. Des. Anal. Manuf. 24, 483–505 (2010)CrossRefGoogle Scholar
  2. 2.
    Vincent, J.F.V., et al.: Biomimetics: its practice and theory. J. R. Soc. Interface 3(9), 471–482 (2006)CrossRefGoogle Scholar
  3. 3.
    Chiu, I., Shu, L.H.: Bridging cross-domain terminology. In: ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering (2005)Google Scholar
  4. 4.
    Wegst, U.G.K., Ashby, M.F.: The mechanical efficiency of natural materials. Phil. Mag. 84, 2167–2186 (2004)CrossRefGoogle Scholar
  5. 5.
    Bogatyrev, N.R.: Ecological Engineering of Survival. Publishing house of SB RAS, Novosibirsk (2000)Google Scholar
  6. 6.
    Chakrabarti, A., et al.: A functional representation for aiding biomimetic and artificial inspiration of new ideas. AIE EDAM 19(02), 113–132 (2005)Google Scholar
  7. 7.
    Stroble, J.K., et al.: Modeling the cellular level of natural sensing with the functional basis for the design of biomimetic sensor technology. In: 2008 IEEE Region 5 Conference. IEEE (2008)Google Scholar
  8. 8.
    Vattam, S., Wiltgen, B., Helms, M., Goel, A., Yen, J.: DANE: fostering creativity in and through biologically inspired design. In: Taura, T., Nagai, Y. (eds.) First International Conference on Design Creativity, pp. 115–122. Springer, London (2011). Scholar
  9. 9.
    Altshuller, G.S.: Creativity as An Exact Science. Gordon & Breach, New York (1988)Google Scholar
  10. 10.
    Vincent, J.F.V., Mann, D.L.: Systematic technology transfer from biology to engineering. Philos. Trans. R. Soc. Lond. A: Math. Phys. Eng. Sci. 360(1791), 159–173 (2002)CrossRefGoogle Scholar
  11. 11.
    Shevkoplyas, S.S., Yoshida, T., Munn, L.L.: Biomimetics design of a microfluidic device for auto-separation of leukocytes from whole blood. Am. Chem. Soc. 77, 933–937 (2005)Google Scholar
  12. 12.
    Wanieck, K., Fayemi, P.-E., Maranzana, N., Zollfrank, C., Jacobs, S.: Biomimetics and its tools. Biomim. Tools 6(2), 53–66 (2017)Google Scholar
  13. 13.
    Baumeister, D., Tocke, R., Dwyer, J., Ritter, S.: Biomimicry Resource Handbook: A Seed Bank of Best Practices. Biomimicry 3.8, Missoula (2013)Google Scholar
  14. 14.
    Deldin, J.-M., Schuknecht, M.: The AskNature database: enabling solutions in biomimetic design. In: Goel, A.K., McAdams, D.A., Stone, R. (eds.) Biologically Inspired Design, pp. 17–27. Springer, London (2014). Scholar
  15. 15.
    Hooker, G., Smith, E.: AskNature and the biomimicry taxonomy. Insight 19(1), 46–49 (2016)CrossRefGoogle Scholar
  16. 16.
    Fayemi, P.E., Wanieck, K., Zollfrank, C., Maranzana, N., Aoussat, A.: Biomimetics: process, tools and practice. Bioinspiration Biomim. 12(1), 011002 (2017)CrossRefGoogle Scholar
  17. 17.
    Jacobs, S.R., Nichol, E.C., Helms, M.E.: Where are we now and where are we going? The BioM innovation database. J. Mech. Des. 136(11), 111101 (2014)CrossRefGoogle Scholar
  18. 18.
    Vandevenne, D., Verhaegen, P.A., Dewulf, S., Duflou, J.R.: Product and organism aspects for scalable systematic biologically-inspired design. Procedia Eng. 131, 784–791 (2015)CrossRefGoogle Scholar
  19. 19.
    Nagel, R.L., et al.: Exploring the use of functional models in biomimetic conceptual design. J. Mech. Des. 130(12), 121102 (2008)CrossRefGoogle Scholar
  20. 20.
    Helms, M., Vattam, S.S., Goel, A.K.: Biologically inspired design: process and products. Des. Stud. 30(5), 606–622 (2009)CrossRefGoogle Scholar
  21. 21.
    Bogatyreva, O., Shillerov, A., Bogatyrev, N.: Patterns in TRIZ contradiction matrix: integrated and distributed systems. In: Proceedings of ETRIA World Conference TRIZ Future 2004, Florence, Italy, 5 November 2004Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2018

Authors and Affiliations

  • Davide Russo
    • 1
  • Pierre-Emmanuel Fayemi
    • 2
    Email author
  • Matteo Spreafico
    • 1
  • Giacomo Bersano
    • 2
  1. 1.Bergamo UniversityDalmineItaly
  2. 2.IKOS ConsultingLevallois-PerretFrance

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