본문 바로가기
  • Home

Building the Outlier Candidate Discrimination Training Data based on Inventory for Automatic Classification of Transferred Records

  • Journal of Korean Society of Archives and Records Management
  • Abbr : JRMASK
  • 2022, 22(1), pp.43~59
  • DOI : 10.14404/JKSARM.2022.22.1.043
  • Publisher : Korean Society of Archives and Records Management
  • Research Area : Interdisciplinary Studies > Library and Information Science > Archival Studies / Conservation
  • Received : February 9, 2022
  • Accepted : February 7, 2022
  • Published : February 28, 2022

Jeong Jihye 1 Lee, Gemma 2 Hosung Wang 2 Hyo-Jung Oh 1

1전북대학교
2국가기록원

Accredited

ABSTRACT

Electronic public records are classified simultaneously as production, a preservation period is granted, and after a certain period, they are transferred to an archive and preserved. This study intends to find a way to improve the efficiency in classifying transferred records and maintain consistent standards. To this end, the current record classification work process carried out by the National Archives of Korea was analyzed, and problems were identified. As a way to minimize the manual work of record classification by converging the required improvement, the process of identifying outlier candidates based on a list consisting of classified information of the transferred records was proposed and systemized. Furthermore, the proposed outlier discrimination process was applied to the actual records transferred to the National Archives of Korea. The results were standardized and constructed as a training data format that can be used for machine learning in the future.

Citation status

* References for papers published after 2023 are currently being built.

This paper was written with support from the National Research Foundation of Korea.