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Conference Papers Year : 2018

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

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Pierre-Emmanuel Fayemi
  • Function : Author
  • PersonId : 1053438
Giacomo Bersano
  • Function : Author

Abstract

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.
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Dates and versions

hal-02279772 , version 1 (05-09-2019)

Licence

Attribution - CC BY 4.0

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Cite

Davide Russo, Pierre-Emmanuel Fayemi, Matteo Spreafico, Giacomo Bersano. Design Entity Recognition for Bio-inspired Design Supervised State of the Art. 18th TRIZ Future Conference (TFC), Oct 2018, Strasbourg, France. pp.3-13, ⟨10.1007/978-3-030-02456-7_1⟩. ⟨hal-02279772⟩
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