Protecting Privacy in the Archives: Supervised Machine Learning and Born-Digital Records

摘要

This paper documents the iterations attempted in developing training sets for supervised machine learning relating to identification of documents relating to human resources and containing personal information. Overall, these results show promise, although we have so far been unable to propose a more systematic approach to developing training sets. This suggests that supervised machine learning could be a viable approach for a "triage" method of reviewing collection for restrictions.