Automatic Extraction of Potentially Contradictory Parameters from Specific Field Patent Texts

Résumé

Nowadays, Altshuller contradiction matrix is used by many TRIZ practitioners, especially by beginners, thanks to its simplicity. However, establishing the link between user’s specific problems issued from their experience in their domain of knowledge makes the use of the matrix often difficult. Applying specific terms of domain to formalized language of TRIZ tools necessitate an expertise that users often don’t have time to build. Our previous finding based on Natural Languages Processing (NLP) tools and techniques, made possible to process a corpus of patents from a given field and thanks to Topic Modelling technique we achieved to link the technical parameters extracted out of patents to their context representation on a vector space in the text. However, this approach is not pertinent to identify the contradictory relations between extracted parameters. For this reason, we applied antonyms identification technique in order to better process the relations of oppositions between extracted parameters. The goal of this research it to extract automatically potential contradictions and set them up in an Altshuller-like matrix. Such an approach could facilitate the application of this famous TRIZ tool for practical user’s problems. Moreover, setting up the matrix for patents of the new domain of knowledge could help to construct easily the state of art for these types of domain and keep the users informed without spending a lot of time and human resources for reading and analyzing large quantities of texts appearing continuously in each domains.

BibTeX

@inproceedings{berdyugina:hal-04067820,
  TITLE = {{Automatic Extraction of Potentially Contradictory Parameters from Specific Field Patent Texts}},
  AUTHOR = {Berdyugina, Daria and Cavallucci, Denis},
  URL = {https://inria.hal.science/hal-04067820},
  NOTE = {Part 2: TRIZ, Intellectual Property and Smart Technologies},
  BOOKTITLE = {{TRIZ Future conference}},
  ADDRESS = {Bolzano, Italy},
  EDITOR = {Yuri Borgianni and Stelian Brad and Denis Cavallucci and Pavel Livotov},
  PUBLISHER = {{Springer International Publishing}},
  SERIES = {IFIP Advances in Information and Communication Technology},
  VOLUME = {AICT-635},
  PAGES = {150-161},
  YEAR = {2021},
  MONTH = Sep,
  DOI = {10.1007/978-3-030-86614-3\_12},
  KEYWORDS = {NLP ; Altshuller matrix ; Text mining},
  PDF = {https://inria.hal.science/hal-04067820v1/file/513811_1_En_12_Chapter.pdf},
  HAL_ID = {hal-04067820},
  HAL_VERSION = {v1},
}