Natural Language Processing (NLP) – A Solution for Knowledge Extraction from Patent Unstructured Data-Reference-Cited by-同舟云学术

Natural Language Processing (NLP) – A Solution for Knowledge Extraction from Patent Unstructured Data

Published:2015 Issue: Volume:131 Page:635-643
ISSN:1877-7058
Container-title:Procedia Engineering
language:en
Short-container-title:Procedia Engineering

Author:

Souili Achille,Cavallucci Denis,Rousselot François

Publisher

Elsevier BV

Subject

Applied Mathematics

Reference19 articles.

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3. Cavallucci D, Khomenko N (2007) From TRIZ to OTSM-TRIZ, Addressing complexity challenges in Inventive design. In: International Journal of Product Development.

4. Khomenko, N and Ashtiani, M (2007) Classical TRIZ and OTSM as a scientific theoretical background for non-typical problem solving instruments. In: TRIZ Future Conference 2007, Frankfurt, Germany.

5. Zanni-Merk C, Rousselot F, Cavallucci D (2011) Use of formal ontologies as a foundation for inventive design studies. In: Computers in Industry 01/2011; 62:323-336. pp.323-336.

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