Large-scale graph neural network optimized for human resource matching in the medical and nursing care fields

Toyotaro Suzumura
Graduate School of Information Science and Technology
The shortage of medical and nursing care workers is an urgent issue for the super-aging society, and a more advanced human resource matching mechanism that reflects the respective intentions of the medical and nursing care workers, medical institutions, and nursing care facilities is needed. Using job information and application information (which have been anonymized) from job sites, we will capture it as a dynamic large-scale knowledge graph and realize a graph depth learning-based matching mechanism optimized for the medical and nursing care domain. This is an industry-academia collaborative project.
Job matching system based on knowledge graph
Knowledge graph visualization for job matching

Related links

Research collaborators

  • The University of Tokyo: Satoshi Waki, Hiroki Kanezashi, Masatoshi Hanai
  • SMS Co., Ltd: Shu Kobayashi, Koki Ogai, Masahiko Hasegawa


  • SDG3 Ensure healthy lives and promote well-being for all at all ages
  • SDG8 Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all
  • SDG10 Reduce inequality within and among countries
  • SDG11 Make cities and human settlements inclusive, safe, resilient and sustainable


  • Toyotaro Suzumura
  • Email: suzumura[at]
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