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研究生: 戴衣菱
Yi-Ling Tai
論文名稱: 多個專有詞彙概念解釋句語意關連自動分析組織之研究
Semantic Association Analysis for Organizing Related Sentences of Multiple Domain-Specific Terms
指導教授: 柯佳伶
Koh, Jia-Ling
學位類別: 碩士
Master
系所名稱: 資訊工程學系
Department of Computer Science and Information Engineering
論文出版年: 2010
畢業學年度: 98
語文別: 中文
論文頁數: 71
中文關鍵詞: 資料探勘資訊檢索句子分群自動摘要
英文關鍵詞: Data Mining, Information Retrieval, Sentence Clustering, Automatic Summarization
論文種類: 學術論文
相關次數: 點閱:103下載:2
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  • 本論文研究以電子書作為內容來源,針對兩個特定領域專有詞彙的概念解釋句,進行自動擷取以及分群組織整理。為了克服傳統上使用字詞頻率建構特徵向量卻忽略隱含語意關係的缺點,本論文提出計算句子中出現的所有字詞對選取的特徵字詞之語意相似關係,來對句子建立MI特徵向量,進行句子分群。從分群的結果中選定可以代表分群概念的標籤,使用標籤來重新組織概念架構,並且在分群中挑出可以代表兩個專有詞彙的比較句。

    In this thesis, we use PDF textbook as data resource, focus on comparing the conceptual sentences of two domain-specific terms .We first calculate the mutual information of every word in sentence and selected feature words to build MI vector space model. The vector space model is used to evaluate the similarity of two sentences for the hierarchical clustering algorithm. After clustering, we choose representative labels and comparative sentence pair for every cluster. According representative labels, the clusters which have the same labels will be grouped as a new concept hierarchy.

    目錄 i 附表目錄 ii 附圖目錄 iii 第一章 簡介 1 1.1 研究動機 1 1.2 研究目的 2 1.3 研究的範圍與方法 5 1.4 論文內容的安排 6 第二章 文獻探討 7 2.1 問答系統介紹 7 2.2文件特徵擷取 10 2.3 語意關聯 12 2.4 文件分群與摘要 14 第三章 系統架構與運作流程 16 第四章 資料前處理與索引建立 19 4.1 資料前處理 19 4.2 建立文件索引 23 第五章 解釋句分群 28 5.1 答案句排序 28 5.2 建立解釋句特徵向量 30 5.3 解釋句分群方法 32 第六章 解釋句概念組織方法 36 6.1 分群代表標籤 36 6.2 組織概念分群 37 6.3 比較句挑選 39 第七章 實驗結果與討論 41 7.1 實驗評估 41 7.2 分析與討論 49 第八章 結論與未來研究 52 參考文獻 53

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