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Latent semantic extraction and analysis for TRIZ-based inventive design

Author

Listed:
  • Wei Yan
  • Hong Liu
  • Yusheng Liu
  • Jihua Wang
  • Cecilia Zanni-Merk
  • Denis Cavallucci
  • Xiaodan Yan
  • Liang Zhang

Abstract

During the development of TRIZ, several knowledge sources have been developed to solve inventive problems. Even though they are about close notions, the level of detail of the descriptions is very dissimilar, making it difficult for the user to operate with them in a systematic way. To cope with this difficulty, we are interested in finding semantic links among these sources, with the goal of assisting the inventive design expert during his activities. Taking into account that all the TRIZ knowledge sources are represented as short texts and directly applying conventional topic models on such short texts may not work well, an extended latent semantic analysis model is proposed to find the missing links among the TRIZ knowledge sources. With the help of these obtained links, several heuristic abstract solutions can be obtained. In order to show this whole process, the resolution of the case of the 'Auguste Piccard's Stratostat' is elaborated in detail. [Received: 11 March 2017; Revised: 21 November 2017; Accepted 30 March 2018]

Suggested Citation

  • Wei Yan & Hong Liu & Yusheng Liu & Jihua Wang & Cecilia Zanni-Merk & Denis Cavallucci & Xiaodan Yan & Liang Zhang, 2018. "Latent semantic extraction and analysis for TRIZ-based inventive design," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 12(5), pages 661-681.
    • Handle: RePEc:ids:eujine:v:12:y:2018:i:5:p:661-681
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