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研究生： 余駿
Chun Yu
論文名稱： 本體論為基之智慧型專利文件自動摘要方法論研究
A Novel Methodology for Automated Ontology-Based Patent Document Summarization
指導教授： 張瑞芬
口試委員:
學位類別： 碩士
Master
系所名稱： 工學院 - 工業工程與工程管理學系
Department of Industrial Engineering and Engineering Management
論文出版年： 2006
畢業學年度： 94
語文別： 中文
論文頁數： 132
中文關鍵詞： 本體論 、摘要系統 、專利文件 、關鍵詞彙擷取 、文字探勘
外文關鍵詞： Ontology, Summarization system, Patent document, Key-phrases extraction, Text mining
相關次數： 點閱：1  下載：0 
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    • 根據世界智慧財產組（WIPO, 1996）指出，專利資訊是中含有全世界90%~95%的商品化研發成果，相對於其他技術報告或期刊報導僅含有5~10%的核心技術來說，專利文件是唯一能夠完整揭露核心技術的知識文件。經WIPO調查顯示，只要公司能善用專利資訊，將可以節省40%的研發成本以及縮短60%的研發時程，因此，專利文件在知識經濟的時代扮演著極為重要的角色；然而，由於專利文件的日益遽增，人們無法有效地閱讀、組織和充分了解，另外，專利文件中包含了許多技術及法律上的專業詞彙，更增加了專利文件閱讀的困難性，因此，如何有效地組織、理解並從專利文件中擷取出重要的資訊變為知識管理領域中的ㄧ重要課題。在本論文中，我們提出了一個以本體論為基之智慧型專利文件自動摘要系統，並以動力手工具及化學機械研磨領域之知識文件來測試自動摘要系統之成效。首先，系統藉由事先定義好的動力手工具和化學機械研磨本體論樹狀架構以及TF-IDF為基之技術來擷取出專利文件中之領域關鍵字和出現頻率次數較高的字詞，並在擷取出的關鍵字詞基礎上，探勘出內容中重要的詞彙，再依據一遞迴演算法來擷取出重要的多字詞，並將重複的資訊予以整併；接著，由K-Mean分群演算法進行段落分群，將文件中擁有相同概念主題的段落聚集在一起；隨後，利用先前所取出之所有關鍵詞彙來衡量每一段落群集之資訊重要程度以挑選出候選摘要段落；最後，將候選摘要配合事先建置好的模板產出文字形式的摘要。除文字摘要之外，系統會將文件中有對應到的本體論架構樹狀節點的字詞予以標示註解並產出一視覺化圖形形式之樹狀摘要。

    According to the report of World Intellectual Property Organization (WIPO), patent documents are the only type of documents that can totally disclose core techniques, and there are 90% to 95% R&D achievements in commercialization comparing to 5% to 10% disclosure rate of other types of documents (e.g. technical reports, and journal articles). By the investigation of WIPO, as long as a company can make the best use of patent information, it can save R&D costs by 40% and shorten the R&D time by 60%. As a consequence, patent information has been playing an important role in the era of knowledge-based economy. However, the numbers of patent documents are increasing dramatically, and most researchers cannot process, organize and understand them with an effective manner. Moreover, it is increasingly difficult for researchers to fully understand patent documents with a lot of technical and legal vocabularies in the context. In this paper, we propose an ontology-based key-phrase recognition technology for the construction of an automated summarization system. In addition, the patents of Power Hand Tool and Chemical Mechanical Polishing are used to verify the effectiveness of proposed summarization system. First, the system extracts domain key words by using a pre-defined ontology, and uses TF-IDF method to extract high frequency terms. Second, a clustering algorithm, K-Mean, is adopted, and the content with similar concept will be gathered together. Third, the candidate paragraphs are picked up from each cluster by using key words and phrases to measure every paragraph importance in each cluster. Finally, the candidate paragraphs are combined with template that is defied in advance, and the text summary is generated at this stage. In addition, the system will mark, annotate and highlight the nodes of ontology tree that are corresponding to words in the document, and produce a visualized feature of summary.

    中文摘要 I Abstract II 誌謝辭 III 內容目錄 IV 表目錄 VII 圖目錄 IX 1. 緒論 1 1.1 背景 1 1.2 動機和目標 1 1.3 研究方法和步驟 2 1.4 論文組織 3 2. 文獻回顧 4 2.1 本體論 4 2.1.1 定義 4 2.1.2 本體論與語意網 7 2.1.3 以本體論為基之知識管理應用 12 2.2 文字探勘 13 2.2.1 定義 13 2.2.2 關鍵字擷取方法 13 2.2.3 文字探勘在分析專利文件上之應用 19 2.3 文件摘要 21 2.3.1 定義 21 2.3.2摘要流程 21 2.3.3 摘要技術及方法 23 2.4 評估摘要之方法 31 3. 文件自動摘要系統與方法論 34 3.1 方法論程序 34 3.2 系統前置處理 37 3.3 關鍵字擷取 37 3.3.1 文件內容之前處理 38 3.3.2 關鍵詞彙辨識 41 3.3.3 關鍵字詞整併 46 3.4 摘要呈現 47 3.4.1 建立段落相關性矩陣並將段落分群 47 3.4.2 衡量段落之重要性 50 3.4.3 摘要呈現 53 4. 系統分析和設計 55 4.1 軟體和硬體需求 55 4.2 系統功能設計 56 4.3 系統資料庫設計 58 4.4 專利文件自動摘要流程分析與設計 61 4.4.1 文件上傳流程 62 4.4.2 文件內容前處理流程 63 4.4.3 關鍵詞彙解析流程 64 4.4.4 文件自動摘要流程 64 4.5 建立領域知識本體論 65 5. 系統建置及評估 78 5.1 系統建置 78 5.1.1 本體論詞彙維護 79 5.1.2 專利文件上傳 81 5.1.3 關鍵詞彙解析 87 5.1.4 文件自動摘要 88 5.1.5 全文查詢 89 5.1.6 條件值查詢 92 5.2 系統評估 93 5.2.1測試文件之收集 93 5.2.2評估步驟與結果 94 6. 結論 102 6.1 研究結論 102 6.2 未來展望 104 7. 參考文獻 105 附錄 1 – 停字列表 116 附錄 2 – 論文摘要範例(動力手工具) WO 021/4027 119 附錄 3 – 論文摘要範例(化學機械研磨) WO 01/15855 123 附錄 4 – 測試專利文件列表(動力手工具) 127 附錄 5 – 測試專利文件列表(化學機械研磨) 130 表1、本體論的定義 6 表2、RDF語法說明 10 表3、擷取方法之比較 18 表4、以文件集為基礎的摘要方法研究之比較（葉鎮源，2002）25 表5、以段落關係地圖為基的三種選取摘要之方法比較 28 表6、斷詞符號 38 表7、部分的停字表 39 表8、專利全文比對本體論節點的關鍵字 42 表9、專利專利全文比對本體論節點的同義字 43 表10、同義字反饋演算法 44 表11、同義字還原演算法 44 表12、段落與重要詞彙的相關性矩陣 47 表13、兩兩段落間相似度矩陣 49 表14、動力手工具專利分類說明 66 表15、動力手工具領域關鍵字 72 表16、動力手工具領域同義字 72 表17、本體論節點關鍵字所對應之同義字 72 表18、化學機械研磨專利分類說明 73 表19、動力手工具之測試文件 93 表20、化學機械研磨之測試文件 93 表21、資訊壓縮率比較（動力手工具） 94 表22、資訊壓縮率比較（化學機械研磨） 95 表23、資訊保留率比較（動力手工具） 96 表24、本論文系統之召回率、準確率及資訊保留率（動力手工具）96 表25、資訊保留率比較（化學機械研磨） 97 表26、本論文系統之召回率、準確率及資訊保留率（化學機械研磨）97 表27、分類準確率比較（動力手工具） 98 表28、分類準確率比較（化學機械研磨） 99 表29、综合比較 100 表30、與DII摘要結果之比較 101 圖1、論文研究架構和步驟 2 圖2、本體論概念圖 5 圖3、本體論範例說明 5 圖4、可分享性知識的概念說明 6 圖5、Tim Berners-Lee's layer cake（XML conference, 2000）8 圖6、RDF敘述式表示圖 9 圖7、RDF範例敘述式表示 9 圖8、以XML表達RDF編碼 9 圖9、Electricity與Power Source關係圖 11 圖10、以RDF Schema描述Electricity是一種Power Source 11 圖11、研磨墊研磨晶圓 11 圖12、以OWL語法描述Polishing Pad研磨Wafer 12 圖13、自動摘要的流程步驟 22 圖14、以文件集為基礎的摘要技術方法之系統概觀（Kupiec et al., 1995） 24 圖15、自動摘要程序 25 圖16、段落關係地圖相似度連結是意圖 27 圖17、語意鏈結原始文件範例 29 圖18、語意鏈結的視覺化示意圖 30 圖19、方法論程序 36 圖20、原始文件有對應到之節點以藍色表示 42 圖21、關鍵字詞整併示意圖 47 圖22、段落分群結果示意圖 50 圖23、以專利全文比對樹狀節點之結果 51 圖24、群集中各段落分數之計算示意圖 53 圖25、文字形式的摘要 54 圖26、視覺化本體論樹狀摘要 54 圖27、系統模組與功能架構 56 圖28、系統資料庫實體關係模型圖 58 圖29、專利文件自動摘要流程圖 62 圖30、上傳專利文件的細部流程 63 圖31、文件內容前處理 63 圖32、關鍵詞彙解析流程 64 圖33、文件自動摘要流程 65 圖34、動力手工具分類 65 圖35、動力手工具本體論 67 圖36、動力手工具本體論知識地圖 67 圖37、動力手工具本體論架構圖一 68 圖38、手工具本體論架構圖二 68 圖39、力手工具本體論架構圖三 69 圖40、動力手工具本體論架構圖四 70 圖41、動力手工具本體論架構圖五 70 圖42、動力手工具本體論架構圖六 70 圖43、動力手工具本體論架構圖七 71 圖44、化學機械研磨專利分類 73 圖45、化學機械研磨本體論 74 圖46、化學機械研磨本體論知識地圖 74 圖47、化學機械研磨本體論架構圖一 75 圖48、化學機械研磨本體論架構圖二 75 圖49、化學機械研磨本體論架構圖三 76 圖50、化學機械研磨本體論架構圖四 76 圖51、化學機械研磨本體論架構圖五 77 圖52、化學機械研磨本體論架構圖六 77 圖53、系統首頁 78 圖54、系統功能主畫面 79 圖55、本體論樹狀關鍵字新增 79 圖56、本體論樹狀關鍵字修改 80 圖57、本體論樹狀關鍵字刪除 80 圖58、本體論同義字庫新增 81 圖59、本體論同義字庫新增 81 圖60、專利文件上傳 82 圖61、專利資訊之確認 83 圖62、關鍵詞彙解析 83 圖63、關鍵詞彙解析-修改功能 84 圖64、摘要結果-摘要 84 圖65、摘要結果-專利圖檔 85 圖66、摘要結果-專利宣告 85 圖67、摘要結果-專利原始上傳文件 86 圖68、摘要結果-本體論樹狀摘要 86 圖69、摘要結果-段落形成摘要資訊 87 圖70、未經過關鍵詞彙解析文件之列表 87 圖71、未經過自動摘要的文件列表 88 圖72、專利文件詳細資料 89 圖73、全文件檢索 89 圖74、全文檢索文件列表 90 圖75、線上閱覽 90 圖76、專利文件下載 91 圖77、專利文件分析過後相關資訊 91 圖78、摘要呈現結果 92 圖79、文件值查詢 93 圖80、資訊壓縮率比較（動力手工具） 94 圖81、資訊壓縮率比較（化學機械研磨） 95 圖82、資訊保留率比較（動力手工具） 96 圖83、本論文系統之召回率、準確率及資訊保留率（動力手工具） 96 圖84、資訊保留率比較（化學機械研磨） 97 圖85、本論文系統之召回率、準確率及資訊保留率（化學機械研磨） 98 圖86、分類準確率比較（動力手工具） 99 圖87、分類準確率比較（化學機械研磨） 99

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