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Communication Dans Un Congrès Année : 2021

Patent Data Driven Innovation Logic: Textual Pattern Exploration to Identify Innovation Logic Data

Simon Dewulf
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Résumé

This paper introduces, examines and confirms that text patterns that identify properties, functions, values, solutions in patent literature. Text patterns can augment the full innovation logic process. The research proposed the use of adjectives for property identification and verbs for functions. It is furthermore shown that there is a context independent relations between properties and functions, or adjectives and verbs. Specific patterns will be proposed for each step in the innovation logic process. The proposed Innovation Logic process contains three distinct steps; wish, shop and create. Artificial innovation methods can be fueled by using these text patterns in patent data. Patent Data Driven Innovation Logic demonstrates a systematic innovation approach that combines the force of contemporary data mining methods on patent literature, with a structured innovation research methodology. A toothbrush is used as a case study. This paper contains excerpts of the PhD ‘Patent Data Driven Innovation Logic’ [1].
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Dates et versions

hal-04067800 , version 1 (13-04-2023)

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Simon Dewulf, Peter Childs. Patent Data Driven Innovation Logic: Textual Pattern Exploration to Identify Innovation Logic Data. TRIZ Future conference, Sep 2021, Bolzano, Italy. pp.170-181, ⟨10.1007/978-3-030-86614-3_14⟩. ⟨hal-04067800⟩
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