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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/144042

    Title: 中文司法裁判文書標記輔助環境初探
    A Prototype for Assisting the Labeling of Judicial Documents in Chinese
    Authors: 黃翊唐
    Huang, Yi-Tang
    Contributors: 劉昭麟
    Huang, Yi-Tang
    Keywords: 法學資訊
    Legal informatics
    System development
    Natural language processing
    Judicial ruling
    Date: 2023
    Issue Date: 2023-04-06 18:00:07 (UTC+8)
    Abstract:   隨著科技日新月異,許多產業導入各種硬軟體進行自動化與數位化,但是在法學資訊領域上這件事情較難以發展,原因可能是案發原因複雜,難以使用文字完整記載、法官判決之理由也不全然會寫在判決書內,所以法學資訊相較於其他領域較難以發展。我們希望透過將判決書的各種標記,把判決書中的某些類別標記出來,像是:爭點、法官見解等等,將判決書中的線索解構出來,方便進行後續的檢索甚至是機器學習等等應用,本篇論文在研究標記系統的開發方法與相關技術。
      As technology advances, many industries are adopting various software and hardware for automation and data management, but it is difficult to develop in the field of legal informatics. This may be because the reasons for the case are complicated and difficult to fully record in writing, and the reasons for the judge`s ruling are not entirely written in the ruling. Therefore, legal informatics is difficult to develop compared to other fields. We hope to mark the various marks in the ruling, mark out some categories in the ruling, such as: points of contention, judge`s opinion, etc., and deconstruct the clues in the ruling to facilitate subsequent retrieval or even machine learning applications. This paper studies the development methods and related technologies of the labeling system.
      Due to the training and deep learning models with excellent training quality, it depends on a large amount of data to train and test the model. These materials must be manually marked by manual. The error rate and the quality of the data set, we hope to develop a set of judgment auxiliary systems, users can retrieve, browsing, uploading, marking, and download markers on this system to reduce the marking marks. Difficulty, and improve the smoothness of the workflow to reduce the result of reducing error rates.
    Reference: 司法院法學資料檢索系統 (2023)。檢自https://lawsearch.judicial.gov.tw/(January 01, 2023)
    劉一凡、劉昭麟及楊婕。以民事訴訟之爭點分群為基礎的類似案件搜尋系統(Clustering Issues in Civil Judgments for Recommending Similar Cases),第卅四屆自然語言與語音處理研討會論文集 (ROCLING XXXIV),184-192。2022。
    預測 (Predicting judgments and grants for civil cases of alimony for the elderly), 第卅四屆自然語言與語音處理研討會論文集 (ROCLING XXXIV),121-128。2022。
    書結構 (Using machine learning and pattern-based methods for identifying elements in Chinese judgment documents of civil cases),第卅四屆自然語言與語音處理研討會論文集 (ROCLING XXXIV),107-115。2022。
    Elasticsearch. Retrieved from https://www.elastic.co/ (January 01, 2023)
    黃詩淳、邵軒磊,人工智慧與法律資料分析之方法與應用:以單獨親權酌定裁判的預測模型為例。臺大法學論叢,第 48 卷第 4 期,2023-2073。2019。
    司 法 院 : 國 民 法 官 制 度 (2023)。檢自https://social.judicial.gov.tw/CJlandingpage/ (February 03, 2023)
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    Chen, Irene Y., Rahul G. Krishnan, and David Sontag. Clustering Interval-Censored Time-Series for Disease Phenotyping. Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 36, No. 6, 6211-6221. 2022.
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    Huang, Yi-Tang, Hong-Ren Lin, and Chao-Lin Liu. Toward an Integrated Annotation and Inference Platform for Enhancing Justifications for Algorithmically Generated Legal Recommendations and Decisions. Legal Knowledge and Information Systems. IOS Press, 281-285. 2022.
    Description: 碩士
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0108753132
    Data Type: thesis
    Appears in Collections:[Department of Computer Science ] Theses

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