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題名 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
作者 廖鼎銘
Lia, Ting-Ming
貢獻者 劉昭麟
Liu, ChaoLin Liu
廖鼎銘
Lia, Ting-Ming
關鍵詞 法資訊學
日期 2004
上傳時間 17-Sep-2009 13:55:07 (UTC+8)
摘要 吾人延續電腦簡易刑事判決技術的研究經驗，以有詞序的關鍵詞做為文件的主要特徵，以instance-based reasoning為核心，並結合其它的推論方法，建立一個混合型的案例式推論系統，來分類賭博以及竊盜的刑事案件。此系統以訓練用案件建立判例資料庫；以introspective learning處理機器學習過程中，對不相干和不正確特徵敏感的問題；以訓練過程中的紀錄，過濾判例資料庫中容易造成錯誤分類的instances；最後還導入專家知識建立法則，幫助案件的分類。實驗結果顯示，新的分類方法在竊盜案件上有良好的表現。
為了幫助未來其它的案件之處理工作，本論文還提出一個自動標記賭博案件語意段落的方法，以朝結構化案件的目標前進。該方法根據關鍵詞特徵建立每種段落的模型，包括起始句與結尾句的規則，再根據段落模型自動標記出段落。實驗結果顯示，語意段落的自動標記值得以其它案由的案件進行嘗試。
參考文獻 [1] V. Aleven, Teaching Case-Based Argumentation Through a Model and Examples, Ph.D. Dissertation, University of Pittsburgh.
[2] K. Al-Kofahi, A. Tyrrell, A. Vachher, and P. Jackson, A Machine Learning Approach to Prior Case Retrieval, Proceedings of the 8th International Conference on Artificial Intelligence and Law, 88-93, 2001.
[3] Bonzano, P. Cunningham, and B. Smyth, Using Introspective Learning to Improve Retrieval in CBR: A Case Study in Air Traffic Control, Proceedings of the 2nd International Conference on Case-Based Reasoning, 291-302, 1997.
[4] G. Boella, L. Favali, and L. Lesmo, An Action-Based Ontology of Legal Relations, Proceedings of the 18th International Conference on Artificial Intelligence and Law, 227-228. 2001.
[5] S. Brüninghaus and K. D. Ashley, Predicting the Outcome of Case-Based Legal Arguments, Proceedings of the 9th International Conference on Artificial Intelligence and Law, 233-242, 2003.
[6] S. Brüninghaus and K. D. Ashley, Improviing the Representation of Legal Case Texts With Information Extraction Methods, Proceedings of the 8th International Conference on Artificial Intelligence and Law, 42-51, 2001.
[7] L. K. Branting, J. C. Lester, and C. B. Callaway, Automating Judicial Document Drafting：A Discourse-Based Approach, Artificial Intelligence and Law, 62-64, 1998.
[8] S. Fox and D. B. Leake, Learning to Refine Indexing by Introspective Reasoning, Proceedings of the 1st International Conference on Case-Based Reasoning, 431-440, 1995.
[9] S. Fox and D. B. Leake, Modeling Case-based Planning for Repairing Reasoning Failures, Proceedings of the AAAI Spring Symposium on Representing Mental States and Mechanisms, 31-38, 1995.
[10] D. S. Hirschberg, A Linear Space Algorithm for Computing Maximal Common Subsequence, Communications of the ACM, 341-343, 1975.
[11] D. S. Hirschberg, Algorithms for the Longest Common Subsequence Problem, Journal of the ACM, 664-675, 1977.
[12] T. Kohonen, The Self-Organizing Map, Proceedings of the IEEE, 1464-1480, 1990.
[13] J. Kolodner and D. Leake, A Tutorial Introduction to Case-Based Reasoning, D. Leake, Editor, Case-Based Reasoning：Experiences, Lessons, ＆ Future Directions, 31-65, 1966.
[14] G. Lame, A Categorization Method for French Legal Documents on the Web, Proceedings of the 18th International Conference on Artificial Intelligence and Law, 168-170, 2001.
[15] 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), 783-800, 2004.
[16] T. Mitchell, Instance-Based Learning, Machine Learning, 1997.
[17] K. Pal, An Approach to Legal Reasoning Based on a Hybrid Decision-Support System, Expert Systems with Applications, 1-12, 1999.
[18] F. Provost and J. Aronis, Scaling up inductive learning with massive parallelism, Machine Learning, 23, 33-46, 1996.
[19] E. L. Rissland and K. D. Ashley, A Case-Based System for Trade Secrets Law, Proceedings of the 1st International Conference on Artificial Intelligence and Law, 60-66, 1987.
[20] U. J. Schild, Intelligent Computer Systems for Criminal Sentencing, Proceedings of the 15th International Conference on Artificial Intelligence and Law, 229-238, 1995.
[21] E. Schweighofer, A. Rauber, M. Dittenbach, Automatic Text Representation, Classification and Labeling in European Law, Proceedings of the 18th International Conference on Artificial Intelligence and Law, 78-87, 2001.
[22] B. Verheij, Automated Argument Assistance for Lawyers, Proceedings of the 7th international conference on Artificial intelligence and law, 43-52, 1999.
[23] Case-Based Reasoning：A Review, the AI-CBR Homepage, http://www.ai-cbr.org/classroom/cbr-review.html.
[24] 陳起行, 德國法資訊學, 法學叢刊, 46(2):79-85, 2001.
[25] 司法院法學資料全文檢索 http://nwjirs.judicial.gov.tw/Index.htm.
描述 碩士
國立政治大學
資訊科學學系
91753026
93
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0091753026
資料類型 thesis
dc.contributor.advisor 劉昭麟zh_TW
dc.contributor.advisor Liu, ChaoLin Liuen_US
dc.contributor.author (Authors) 廖鼎銘zh_TW
dc.contributor.author (Authors) Lia, Ting-Mingen_US
dc.creator (作者) 廖鼎銘zh_TW
dc.creator (作者) Lia, Ting-Mingen_US
dc.date (日期) 2004en_US
dc.date.accessioned 17-Sep-2009 13:55:07 (UTC+8)-
dc.date.available 17-Sep-2009 13:55:07 (UTC+8)-
dc.date.issued (上傳時間) 17-Sep-2009 13:55:07 (UTC+8)-
dc.identifier (Other Identifiers) G0091753026en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/32643-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊科學學系zh_TW
dc.description (描述) 91753026zh_TW
dc.description (描述) 93zh_TW
dc.description.abstract (摘要) 吾人延續電腦簡易刑事判決技術的研究經驗，以有詞序的關鍵詞做為文件的主要特徵，以instance-based reasoning為核心，並結合其它的推論方法，建立一個混合型的案例式推論系統，來分類賭博以及竊盜的刑事案件。此系統以訓練用案件建立判例資料庫；以introspective learning處理機器學習過程中，對不相干和不正確特徵敏感的問題；以訓練過程中的紀錄，過濾判例資料庫中容易造成錯誤分類的instances；最後還導入專家知識建立法則，幫助案件的分類。實驗結果顯示，新的分類方法在竊盜案件上有良好的表現。
為了幫助未來其它的案件之處理工作，本論文還提出一個自動標記賭博案件語意段落的方法，以朝結構化案件的目標前進。該方法根據關鍵詞特徵建立每種段落的模型，包括起始句與結尾句的規則，再根據段落模型自動標記出段落。實驗結果顯示，語意段落的自動標記值得以其它案由的案件進行嘗試。		zh_TW
dc.description.tableofcontents 第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究方法 3
1.3 研究成果 4
1.4 論文架構 5
第二章 文獻回顧 6
2.1 推論系統於法律文件上的應用 6
2.2 法律文件的表述方法 9
第三章 背景知識 12
3.1 刑事案件判決書簡介 12
3.2 以詞序為主的輔助判決系統簡介 14
3.3 以詞序為主的輔助判決系統之演算法 16
3.4 資料來源 18
3.5 實驗的評估方法 19
3.6 判決書的前處理 19
第四章 輔助判決系統 22
4.1 設計動機與系統概述 22
4.2 建立判例資料庫 24
4.2.1 Instance之結構與建立 24
4.2.2 訓練instances 25
4.3 Introspective Learning 27
4.3.1 取得instances的投票行為 27
4.3.2 更新instances的內含資訊 30
4.3.3 調整特徵關鍵詞權重 31
4.4 分類方法 37
4.5 filtering procedure 39
第五章 輔助判決系統之實驗結果與分析 41
5.1 實驗資料 41
5.2 實驗參數之測試 43
5.3 實驗結果 46
5.4 實驗分析與討論 47
第六章 結合rule-based的方法 51
6.1 導入domain knowledge 51
6.2 Rule的建立與應用 52
6.3 實驗與分析 53
第七章 賭博案件語意段落的自動標記 55
7.1 「事實」欄位段落結構 55
7.2 段落模型 57
7.3 系統架構 58
7.4 建立判例資料庫 59
7.4.1 標示出語意段落 60
7.4.2 取得特徵關鍵詞集合 60
7.4.3 建立instances 66
7.5 語意段落的自動標記 74
7.5.1 標記段落起始句 77
7.5.2 標記段落結尾句 78
7.5.3 結合重疊段落 80
第八章 語意段落標記系統之實驗結果與分析 86
8.1 實驗資料 86
8.2 實驗結果 86
8.3 實驗分析與討論 88
第九章 結論與未來工作 91
參考文獻 93
附錄：語意段落之實例 95		zh_TW
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dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0091753026en_US
dc.subject (關鍵詞) 法資訊學zh_TW
dc.title (題名) 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zh_TW
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) [1] V. Aleven, Teaching Case-Based Argumentation Through a Model and Examples, Ph.D. Dissertation, University of Pittsburgh.zh_TW
dc.relation.reference (參考文獻) [2] K. Al-Kofahi, A. Tyrrell, A. Vachher, and P. Jackson, A Machine Learning Approach to Prior Case Retrieval, Proceedings of the 8th International Conference on Artificial Intelligence and Law, 88-93, 2001.zh_TW
dc.relation.reference (參考文獻) [3] Bonzano, P. Cunningham, and B. Smyth, Using Introspective Learning to Improve Retrieval in CBR: A Case Study in Air Traffic Control, Proceedings of the 2nd International Conference on Case-Based Reasoning, 291-302, 1997.zh_TW
dc.relation.reference (參考文獻) [4] G. Boella, L. Favali, and L. Lesmo, An Action-Based Ontology of Legal Relations, Proceedings of the 18th International Conference on Artificial Intelligence and Law, 227-228. 2001.zh_TW
dc.relation.reference (參考文獻) [5] S. Brüninghaus and K. D. Ashley, Predicting the Outcome of Case-Based Legal Arguments, Proceedings of the 9th International Conference on Artificial Intelligence and Law, 233-242, 2003.zh_TW
dc.relation.reference (參考文獻) [6] S. Brüninghaus and K. D. Ashley, Improviing the Representation of Legal Case Texts With Information Extraction Methods, Proceedings of the 8th International Conference on Artificial Intelligence and Law, 42-51, 2001.zh_TW
dc.relation.reference (參考文獻) [7] L. K. Branting, J. C. Lester, and C. B. Callaway, Automating Judicial Document Drafting：A Discourse-Based Approach, Artificial Intelligence and Law, 62-64, 1998.zh_TW
dc.relation.reference (參考文獻) [8] S. Fox and D. B. Leake, Learning to Refine Indexing by Introspective Reasoning, Proceedings of the 1st International Conference on Case-Based Reasoning, 431-440, 1995.zh_TW
dc.relation.reference (參考文獻) [9] S. Fox and D. B. Leake, Modeling Case-based Planning for Repairing Reasoning Failures, Proceedings of the AAAI Spring Symposium on Representing Mental States and Mechanisms, 31-38, 1995.zh_TW
dc.relation.reference (參考文獻) [10] D. S. Hirschberg, A Linear Space Algorithm for Computing Maximal Common Subsequence, Communications of the ACM, 341-343, 1975.zh_TW
dc.relation.reference (參考文獻) [11] D. S. Hirschberg, Algorithms for the Longest Common Subsequence Problem, Journal of the ACM, 664-675, 1977.zh_TW
dc.relation.reference (參考文獻) [12] T. Kohonen, The Self-Organizing Map, Proceedings of the IEEE, 1464-1480, 1990.zh_TW
dc.relation.reference (參考文獻) [13] J. Kolodner and D. Leake, A Tutorial Introduction to Case-Based Reasoning, D. Leake, Editor, Case-Based Reasoning：Experiences, Lessons, ＆ Future Directions, 31-65, 1966.zh_TW
dc.relation.reference (參考文獻) [14] G. Lame, A Categorization Method for French Legal Documents on the Web, Proceedings of the 18th International Conference on Artificial Intelligence and Law, 168-170, 2001.zh_TW
dc.relation.reference (參考文獻) [15] 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), 783-800, 2004.zh_TW
dc.relation.reference (參考文獻) [16] T. Mitchell, Instance-Based Learning, Machine Learning, 1997.zh_TW
dc.relation.reference (參考文獻) [17] K. Pal, An Approach to Legal Reasoning Based on a Hybrid Decision-Support System, Expert Systems with Applications, 1-12, 1999.zh_TW
dc.relation.reference (參考文獻) [18] F. Provost and J. Aronis, Scaling up inductive learning with massive parallelism, Machine Learning, 23, 33-46, 1996.zh_TW
dc.relation.reference (參考文獻) [19] E. L. Rissland and K. D. Ashley, A Case-Based System for Trade Secrets Law, Proceedings of the 1st International Conference on Artificial Intelligence and Law, 60-66, 1987.zh_TW
dc.relation.reference (參考文獻) [20] U. J. Schild, Intelligent Computer Systems for Criminal Sentencing, Proceedings of the 15th International Conference on Artificial Intelligence and Law, 229-238, 1995.zh_TW
dc.relation.reference (參考文獻) [21] E. Schweighofer, A. Rauber, M. Dittenbach, Automatic Text Representation, Classification and Labeling in European Law, Proceedings of the 18th International Conference on Artificial Intelligence and Law, 78-87, 2001.zh_TW
dc.relation.reference (參考文獻) [22] B. Verheij, Automated Argument Assistance for Lawyers, Proceedings of the 7th international conference on Artificial intelligence and law, 43-52, 1999.zh_TW
dc.relation.reference (參考文獻) [23] Case-Based Reasoning：A Review, the AI-CBR Homepage, http://www.ai-cbr.org/classroom/cbr-review.html.zh_TW
dc.relation.reference (參考文獻) [24] 陳起行, 德國法資訊學, 法學叢刊, 46(2):79-85, 2001.zh_TW
dc.relation.reference (參考文獻) [25] 司法院法學資料全文檢索 http://nwjirs.judicial.gov.tw/Index.htm.zh_TW