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| Title: | 階層式分群法在民事裁判要旨分群上之應用
An Application of Hierarchical Clustering of Documents for Civil Judgments |
| Authors: | 何君豪
Ho,Jim How |
| Contributors: | 劉昭麟
高照明
Liu,Chao Lin
Gao,Zhao Ming
何君豪
Ho,Jim How |
| Keywords: | 人工智慧與法律
階層式分群法
聚合法
分群
AI&Law
Hierarchical Method
Agglomerative Approach
Cluster |
| Date: | 2006 |
| Issue Date: | 2009-09-17 13:51:58 (UTC+8) |
| Abstract: | 司法院經常聘請資深的法官將民事裁判中具有參考價值的法律意見摘錄出來，製作成民事裁判要旨，民事裁判要旨可作為法官審理類似案件時的辦案參考，因此，在司法實務上民事裁判的搜尋為不可或缺的工作。然隨著資訊科技的發達及裁判數量的累積，民裁判要旨的搜尋結果可能多達數百篇，造成法官須耗費大量的時間在民事裁判要旨的閱讀上，如果能利用資料探勘的技術將搜尋到的民事裁判要旨加以分群，且分群的正確性又可達到一定旳水準，便可節省法官閱讀民事裁判要旨的時間。在本研究中我們嘗試將資料探勘技術中的階層式分群法應用在民事裁判要旨的分群上，並將法律條文所出現的用語作為加權的主關鍵字評估可否改善分群的效果，以探討資料探勘技術中的階層式分群法應用在民事裁判要旨分群上的可行性與成效。
Judicial Yuan often invites senior civil judges to extract legal opinions from civil judgments for making the purports of civil judgments. The purports of civil judgments can be consulted as trial judges handle the similar cases, therefore, in judicial practices, it is an indispensable work for civil judges to search the purports of civil judgments. However, with the development of information technology and the cumulative number of judgments, the number of search results may be as high as hundreds, civil judges must have spent a lot of time reviewing of the purports of civil judgments. If we can utilize data mining technologies to cluster the search results, and the accuracy of clustering can be attained to a certain standard, it will save civil judges a lot of time on reviewing the purports of civil judgments. In this study we attempt to apply hierarchical method on the clustering of the purports of civil judgments, and adjust the weights of main keywords derived from frequently used vocabulary of legal provisions to assess the feasibility and effectiveness of application of hierarchical method on clustering of the purports of civil judgments. |
| Reference: | [1] 司法院法學檢索系統法官版，http://njirs.judicial.gov.tw/Index.htm
[2] 國際人工智慧與法律協會網站,http://www.iaail.org/index.html
[3] HowNet電子詞典1999年版本，http://www.keenage.com/
[4] 林吉鶴，專家系統應用於命案犯罪現場之研究，行政院國科會科資中心NSC84-2414-H015-001，1996。
[5] 洪鵬翔，中文新聞自動群聚，國立清華大學資訊工程學系碩士論文，2000。
[6] 張正宗，電腦輔助簡易刑事判決技術之探討，國立政治大學資訊科學系，碩士論文，台北，台灣，2003。
[7] 郭盛楊，以顧客交易特徵為基礎的顧客分群方法，朝陽科技大學資訊管理系碩士論文，pp.64-66，台中，台灣，2004。
[8] 曾憲雄、蔡秀滿、蘇東興、曾秋蓉、王慶堯，資料探勘，旗標，2005。
[9] 廖鼎銘，觸犯多款法條之賭博與竊盜案件的法院文書的分類與分析，國立政治大學資訊科學系，碩士論文，台北，台灣，2004。
[10] 謝淳達，利用詞組檢索中文訴訟文書之研究，國立政治大學資訊科學系，碩士論文，台北，台灣，2005。
[11] 羅淑娟、柯秀奎，應用Raz & Yaung方法論於文件自動分群，第一屆台灣作業研究會暨2004年科技與管理學研討會，pp.1199-1206，2004。
[12] K. D. Ashley and E. L. Rissland, But, see, accord: Generating Blue Book citations in HYPO, Proc. of the 1st Int`l Conf. on Artificial Intelligence and Law, pp.67-74, 1987.
[13] S. Brüninghaus and K. D. Ashley, Finding factors: Learning to classify case opinions under abstract fact categories, Proceedings of the Sixth International Conference on Artificial Intelligence and Law, pp.123-131, 1997.
[14] S. Brüninghaus and K. D. Ashley, Toward adding knowledge to learning algorithms for indexing legal cases", Proc. of the 7th Int`l Conf. on Artificial Intelligence and Law, pp. 9-17, 1999.
[15] L. Kaufman & P.J. Rousseeuw, Finding Groups in Data: An Introduction to Cluster Analysis, John Wiley & Sons, 1990.
[16] C. L. Liu, C. T. Chang, and J. H. Ho. Classification and clustering for case-based criminal summary judgment, Proceedings of the Ninth International Conference on Artificial Intelligence and Law, pp.252-261, 2003.
[17] C.-L. Liu, C.-T. Chang, and J.-H. Ho. Case instance generation and refinement for case-based criminal summary judgments in Chinese, Journal of Information Science and Engineering 20(4), pp.783-800, 2004.
[18] C. D. Manning & H. Schutze, Foundations of Statistical Natural Language Processing, The MIT Press, 1999.
[19] D.V. McDERMOTT, Temporal Logic for Reasoning about Processes and Plans, Cognitive Science 6, pp101-155, 1982.
[20] H.-T. Pu & L.-F. Chien, Integrating log-based and text-based Methods Towards Automatic Web Htesaurus Construction, supported by the National Science Council (NSC), ROC, under the contract NSC 89-2413-H-128-006.
[21] S. Russel & P. Norvig, Artificial Intelligence - A Modern Approach, Prentice Hall, 1995.
[22] E. Schweighofer & D. Merkl, A learning technique for legal document analysis, Proceedings of the Seventh International Conference on Artificial Intelligence and Law, pp.156-163, 1999.
[23] R. Schalkoff, Similarity measures, matching techniques, and scal-space 14 approaches, Pattern Recognition: Statistical, Structural and Neural Approaches, pp.329-330, John Wiley & sons, Inc., New York, 1992.
[24] O. Zamir and O. Etzioni, Web document clustering: a feasibility demonstration, Proceedings of the 19th International ACM SIGIR Conference on Research and Development in Information Retrieval , pp.46-54, 1998. |
| Description: | 碩士
國立政治大學
資訊科學學系
89753005
95 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0089753005 |
| Data Type: | thesis |
| Appears in Collections: | [資訊科學系] 學位論文
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