2020 Fiscal Year Annual Research Report
Research on Knowledge Extraction from Ancient Mongolian Historical Documents using Deep Learning
| Project/Area Number |
17K00457
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| Research Institution | Ritsumeikan University |
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Principal Investigator |
バトジャルガル ビルゲサイハン 立命館大学, 衣笠総合研究機構, 研究員 (30725396)
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| Project Period (FY) |
2017-04-01 – 2021-03-31
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| Keywords | historical documents / traditional Mongolian / machine learning / deep learning |
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| Outline of Annual Research Achievements |
In the FY2020, 1) continues experiments were conducted to check the accuracy of the proposed deep learning model and 2) the development of the proposed method was continued. In the FY2020, Travel restrictions on the rapid spread of coronavirus disease 2019 (COVID-19), the entry prohibition to the University, and inaccessibility to research facilities were slowing down this research. Although the planned user evaluations that were expected to be conducted by the experts and humanities researchers both in Japan and Mongolia were delayed significantly and the results and feedbacks were not obtained as planned due to Novel Coronavirus (2019-nCoV) spreads, we took some assistances of users remotely on a part-time basis.
Based on the research results obtained in the previous years, I developed and improved a web-based system. The extracted deep learning results are utilized for building digital text representations of manuscripts. Further improvements of the system needs be carried using the evaluation results and user feedback. Research results and achievements have been published in parts in several International conference papers.
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