%0 Conference Proceedings
%T Automatic Extraction of IDM-Related Information in Scientific Articles and Online Science News Websites
%+ Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube)
%A Nédey, Oriane
%A Souili, Achille
%A Cavallucci, Denis
%Z Part 6: TRIZ and Patenting
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 18th TRIZ Future Conference (TFC)
%C Strasbourg, France
%Y Denis Cavallucci
%Y Roland De Guio
%Y Sebastian Koziołek
%I Springer International Publishing
%3 Automated Invention for Smart Industries
%V AICT-541
%P 213-224
%8 2018-10-29
%D 2018
%R 10.1007/978-3-030-02456-7_18
%K TRIZ
%K IDM
%K Inventive Design
%K Machine learning
%K Knowledge extraction
%K Text mining
%K NLP
%Z Computer Science [cs]Conference papers
%X Previous studies have made it possible to extract information related to IDM (Inventive Design Method) out of patents. IDM is an ontology-defined method derived from TRIZ. As its mother theory, IDM is primarily based on patent’s observation and aims at finding inventive solutions on the basis of contradictions. In this paper, we present a new approach for extracting knowledge, this time out of other types of science-related documents: scientific papers and science news articles. This approach is based on sets of linguistics features which have been selected and evaluated semi-automatically with techniques of Natural Language Processing as well as Machine Learning.
%G English
%Z TC 5
%2 https://inria.hal.science/hal-02279756/document
%2 https://inria.hal.science/hal-02279756/file/474537_1_En_18_Chapter.pdf
%L hal-02279756
%U https://inria.hal.science/hal-02279756
%~ INSERM
%~ CNRS
%~ ENGEES
%~ UNIV-STRASBG
%~ INSA-STRASBOURG
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-TC5
%~ INC-CNRS
%~ AGREENIUM
%~ SITE-ALSACE
%~ INSA-GROUPE
%~ IFIP-AICT-541
%~ IFIP-TFC
%~ TEST2-HALCNRS