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Communication Dans Un Congrès Année : 2013

Analysis of Patents for Prior Art Candidate Search

Résumé

In this paper, we describe a method for analyzing a collection of patents in order to help prior art candidate search in an interactive and graphical way. The method relies on the use of two data mining methods: hierarchical agglomerative clustering and principal component analysis, which are applied successively. The correlation between the application patent and the other patents is a good indicator to help decide the classes of patents to look at.
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Dates et versions

hal-04083373 , version 1 (27-04-2023)

Identifiants

  • HAL Id : hal-04083373 , version 1
  • OATAO : 12689

Citer

Sébastien Dejean, Nicolas Faessel, Lucille Marty, Josiane Mothe, Samantha Sadala, et al.. Analysis of Patents for Prior Art Candidate Search. 3rd International Conference on Advances in Information Mining and Management (IMMM 2013), Nov 2013, Lisbonne, Portugal. pp.1-6. ⟨hal-04083373⟩
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