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Automatic classification of patent documents for TRIZ users

Author

Listed:
  • Loh, Han Tong
  • He, Cong
  • Shen, Lixiang

Abstract

In contrast to traditional inventors, inventors using TRIZ are not only interested in searching for prior art in related fields, but also for the analogous inventions in other fields that have solved the same Technical Contradiction by using the same method. To be useful for TRIZ users, patents are required to be classified by the Contradiction they solved and Inventive Principles they used instead of the fields in which they are involved. Most of the currently available automatic patent classification systems are based on technology-dependent schemes such as the IPC and they cannot satisfy TRIZ users' requirements. In this paper, an automatic patent classification for TRIZ users is proposed and explained in detail. In a preliminary study, patent documents were collected for 6 out of 40 Inventive Principles, and the proposed automatic classification tested.

Suggested Citation

  • Loh, Han Tong & He, Cong & Shen, Lixiang, 2006. "Automatic classification of patent documents for TRIZ users," World Patent Information, Elsevier, vol. 28(1), pages 6-13, March.
    • Handle: RePEc:eee:worpat:v:28:y:2006:i:1:p:6-13
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    Cited by:

    1. Suominen, Arho & Toivanen, Hannes & Seppänen, Marko, 2017. "Firms' knowledge profiles: Mapping patent data with unsupervised learning," Technological Forecasting and Social Change, Elsevier, vol. 115(C), pages 131-142.
    2. Jie Hu & Shaobo Li & Jianjun Hu & Guanci Yang, 2018. "A Hierarchical Feature Extraction Model for Multi-Label Mechanical Patent Classification," Sustainability, MDPI, vol. 10(1), pages 1-22, January.

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