| 研究課題/領域番号 |
21K12600
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| 研究種目 |
基盤研究(C)
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| 配分区分 | 基金 |
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| 応募区分 | 一般 |
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| 審査区分 |
小区分90020:図書館情報学および人文社会情報学関連
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| 研究機関 | 立命館大学 |
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研究代表者 |
美龍 硬幸 (バトジャルガル ビルゲサイハン) 立命館大学, 総合科学技術研究機構, プロジェクト研究員 (30725396)
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| 研究期間 (年度) |
2021-04-01 – 2025-03-31
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| 研究課題ステータス |
交付 (2023年度)
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| 配分額 *注記 |
4,160千円 (直接経費: 3,200千円、間接経費: 960千円)
2024年度: 780千円 (直接経費: 600千円、間接経費: 180千円)
2023年度: 910千円 (直接経費: 700千円、間接経費: 210千円)
2022年度: 1,300千円 (直接経費: 1,000千円、間接経費: 300千円)
2021年度: 1,170千円 (直接経費: 900千円、間接経費: 270千円)
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| キーワード | deep learning / legal documents / text classification / Mongolian / deep learming / machine learning / text mining |
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| 研究開始時の研究の概要 |
Recently, numerous Mongolian legal documents have been made digitally public. Nevertheless, analysis of these documents has not been done due to the lack of Mongolian Natural Language Processing (NLP) tools. A reliable computerized analysis is necessary, which requires developing an innovative method for analyzing these documents. Manual reading and analyzing documents are not effective, on a massive scale. Demands are growing for precise analysis of legal documents, hence an artificial intelligence (AI) system that aids expert decisions that clarify conflicts and disputes is essential.
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| 研究実績の概要 |
In the FY2023, the following tasks have been performed: 1) collecting and preparing datasets, 2) proposing deep learning models for Mongolian legal documents and, 3) enhancing the web-based system.
Regarding the datasets, a natural language interface (NLI) dataset was prepared manually by selecting 829 questions related to Mongolian civil law from the Mongolian bar exam questions. We also proposed deep-learning-based models for recognizing textual inference in the Mongolian language and experiments were conducted.
Moreover, in the FY2023, based on the research results obtained in the past, we enhanced our web-based system to integrate for recognizing textual inference in the Mongolian legal documents.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
Our research has been conducted according to the research plan. As planned, the achievements in the FY2023 allowed advancing my research towards to the research goal in developing a deep-learning-based method to analyze Mongolian legal documents. Surveys were conducted in Mongolia, as well as feedback and data were obtained through business trips. Research results and achievements have been published in two international journal articles.
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| 今後の研究の推進方策 |
In the FY2024, business trips for 1) conducting evaluations among overseas users, and 2) obtaining analyses and feedbacks will also be conducted.
We are also planning to perform evaluations by several experts at the National University of Mongolia and Ritsumeikan University in Japan. Feedback from the researchers will be received in a timely manner. Users’ evaluation will also be conducted by experts and users. Further improvements of the method will be carried based on the evaluation results and user feedback.
Research assistance of experts and students are necessary on a part-time basis to 1) evaluate the proposed system 2) conduct experiments, and 3) analyze the experimental results.
Feedback from the researchers will be received in a timely manner. Further improvements of the system will be carried out based on the evaluation results and user feedbacks.
Methods and contents that have no copyright issues will be available freely to the public on the Internet during the FY2023-FY2024.
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