Automatic Linkage Model of Classification Systems Based on a Pretraining Language Model for Interconnecting Science and Technology with Job Information

  • Jeong, Hyun Ji (Korea Institute of Science and Technology Information (KISTI)) ;
  • Jang, Gwangseon (Korea Institute of Science and Technology Information (KISTI)) ;
  • Shin, Donggu (Korea Institute of Science and Technology Information (KISTI)) ;
  • Kim, Tae Hyun (Korea Institute of Science and Technology Information (KISTI))
  • Received : 2022.04.27
  • Accepted : 2022.05.17
  • Published : 2022.06.20


For national industrial development in the Fourth Industrial Revolution, it is necessary to provide researchers with appropriate job information. This can be achieved by interconnecting the National Science and Technology Standard Classification System used for management of research activity with the Korean Employment Classification of Occupations used for job information management. In the present study, an automatic linkage model of classification systems is introduced based on a pre-trained language model for interconnecting science and technology information with job information. We propose for the first time an automatic model for linkage of classification systems. Our model effectively maps similar classes between the National Science & Technology Standard Classification System and Korean Employment Classification of Occupations. Moreover, the model increases interconnection performance by considering hierarchical features of classification systems. Experimental results show that precision and recall of the proposed model are about 0.82 and 0.84, respectively.



This research was supported by Korea Institute of Science and Technology Information (KISTI).


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