| dc.contributor.advisor | 劉昭麟 | zh_TW |
| dc.contributor.advisor | Chao-Lin Liu | en_US |
| dc.contributor.author (Authors) | 張正宗 | zh_TW |
| dc.contributor.author (Authors) | Cheng-Tsung Chang | en_US |
| dc.creator (作者) | 張正宗 | zh_TW |
| dc.creator (作者) | Cheng-Tsung Chang | en_US |
| dc.date (日期) | 2001 | en_US |
| dc.date.accessioned | 18-Sep-2009 18:26:03 (UTC+8) | - |
| dc.date.available | 18-Sep-2009 18:26:03 (UTC+8) | - |
| dc.date.issued (上傳時間) | 18-Sep-2009 18:26:03 (UTC+8) | - |
| dc.identifier (Other Identifiers) | G0090753005 | en_US |
| dc.identifier.uri (URI) | https://ah.lib.nccu.edu.tw/item?item_id=37674 | - |
| 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) | 90753005 | zh_TW |
| dc.description (描述) | 90 | zh_TW |
| dc.description.abstract (摘要) | 我們以機器學習(Machine Learning)的方法，建立rule-based與case-based的instances，再藉由這些 instances來判斷起訴書的案由和法條，其最好的正確率只比人工建立的rules與cases所判斷的結果低7%而已。由於在我們最基本的方法中，一個判例就會被建立成一個instance，如此，我們將需要大量的空間來儲存instances，針對這個問題，我們也提出了instances clustering與刪除部份較不重要詞這兩個方法，來降低instances所佔的空間，經過簡化的系統的正確率不但與原本未刪減instances時差不多，還可以減少將近一半左右的儲存空間；而且如果我們將這兩個刪減instances的方法混合使用，甚致可以找到一個更好的解，不但能些微提升正確率，還可以把儲存instances所需的空間，降低為原本的四分之一左右。 | zh_TW |
| dc.description.abstract (摘要) | I apply machine learning techniques to constructing rule-based and case-based reasoning systems. These systems determine the prosecution reasons and applicable articles of lawsuits, and may achieve an accuracy that is just 7% lower than that achieved by a manually-built system. The baseline method constructs one instance for each prior lawsuit, so it takes much space to store all instances. To reduce the storage space, I propose two methods – clustering instance and removing some less important words in instances. The effects of these methods not only maintain the original accuracy, but also reduce the storage space by half. When I integrated all proposed methods, I can even improve the accuracy slightly and reduce the storage space by three quarters. | en_US |
| dc.description.abstract (摘要) | 第一章 緒論 1\r\n1.1 簡介 1\r\n1.2 研究動機及方法 1\r\n1.3 本論文的貢獻 4\r\n1.4 本論文的章節架構 4\r\n第二章 相關論文回顧和評述 5\r\n2.1 法資訊學 5\r\n2.2 自然語言處理 8\r\n2.3 討論 11\r\n第三章 背景知識 14\r\n3.1 中文的法律文件之處理 14\r\n3.2 台灣的簡易刑事判決與資料來源 15\r\n第四章 人工建立的判斷方法 21\r\n4.1 Rule-based的方法 21\r\n4.1.1 Rule的建立與語法規則 21\r\n4.1.2 Rule的應用 24\r\n4.2 Case-based的方法 26\r\n第五章 INSTANCE-BASED LEARNING 29\r\n5.1 資料的前處理 29\r\n5.2 Instance的產生 30\r\n5.3 Instances的應用 33\r\n5.3.1 第一種形態的instances之應用 33\r\n5.3.2 第二種形態的instances之應用 35\r\n5.3.3 第三種形態的instances之應用 36\r\n5.4 Instance Clustering 38\r\n5.5 刪掉instances中較不重要的詞 41\r\n5.6 在instances中加入比重 43\r\n第六章 實驗結果與分析 46\r\n6.1 正確率的計算 48\r\n6.2 Nearest Neighbor與k-Nearest Neighbor 50\r\n6.3 判斷案由之結果與分析 51\r\n6.4 判斷法條之結果與分析 59\r\n6.5 刪掉instances中較不重要的詞之結果與分析 64\r\n6.6 加入比重的方法及混合三種改善instance的方法之結果與分析 69\r\n第七章 結論和展望 84\r\n7.1 結論 84\r\n7.2 未來的展望 86\r\n參考文獻 88 | - |
| dc.description.tableofcontents | 第一章 緒論 1\r\n1.1 簡介 1\r\n1.2 研究動機及方法 1\r\n1.3 本論文的貢獻 4\r\n1.4 本論文的章節架構 4\r\n第二章 相關論文回顧和評述 5\r\n2.1 法資訊學 5\r\n2.2 自然語言處理 8\r\n2.3 討論 11\r\n第三章 背景知識 14\r\n3.1 中文的法律文件之處理 14\r\n3.2 台灣的簡易刑事判決與資料來源 15\r\n第四章 人工建立的判斷方法 21\r\n4.1 Rule-based的方法 21\r\n4.1.1 Rule的建立與語法規則 21\r\n4.1.2 Rule的應用 24\r\n4.2 Case-based的方法 26\r\n第五章 INSTANCE-BASED LEARNING 29\r\n5.1 資料的前處理 29\r\n5.2 Instance的產生 30\r\n5.3 Instances的應用 33\r\n5.3.1 第一種形態的instances之應用 33\r\n5.3.2 第二種形態的instances之應用 35\r\n5.3.3 第三種形態的instances之應用 36\r\n5.4 Instance Clustering 38\r\n5.5 刪掉instances中較不重要的詞 41\r\n5.6 在instances中加入比重 43\r\n第六章 實驗結果與分析 46\r\n6.1 正確率的計算 48\r\n6.2 Nearest Neighbor與k-Nearest Neighbor 50\r\n6.3 判斷案由之結果與分析 51\r\n6.4 判斷法條之結果與分析 59\r\n6.5 刪掉instances中較不重要的詞之結果與分析 64\r\n6.6 加入比重的方法及混合三種改善instance的方法之結果與分析 69\r\n第七章 結論和展望 84\r\n7.1 結論 84\r\n7.2 未來的展望 86\r\n參考文獻 88 | zh_TW |
| dc.language.iso | en_US | - |
| dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0090753005 | en_US |
| dc.subject (關鍵詞) | 自然語言處理 | zh_TW |
| dc.subject (關鍵詞) | 法資訊學 | zh_TW |
| dc.subject (關鍵詞) | Machine Learning | en_US |
| dc.title (題名) | 電腦輔助簡易刑事判決技術之探討 | zh_TW |
| dc.title (題名) | An Exploration of Computer Assisted Criminal Summary Judgments | en_US |
| dc.type (資料類型) | thesis | en |
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