利用語意分析技術以運用相關回饋資訊於文件重排序

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姓名

劉欣宜(Hsin-Yi Liu) 查詢紙本館藏

畢業系所

資訊管理學系

論文名稱

利用語意分析技術以運用相關回饋資訊於文件重排序
(The application of using semantic analysis techniques in relevance feedback to the document re-ranking)

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摘要(中)

過去在向量空間模型相關回饋研究上，多數是使用者對於查詢結果中的相關文件清單，擷取其字頻資訊為回饋結果，又以Rocchio查詢擴張最被廣泛使用，此演算法具有一定水平與效能且經常被應用在各種檢索中，但是否有其他更好判斷相關字詞和過濾不相關字詞方法，一直以來也都是個被高度關注的研究議題。近幾年語意檢索概念蓬勃發展，許多搜尋引擎開始嘗試以使用者查詢和相關文件中字詞語意做為檢索依據，這種機制主要著重在關鍵字上所涵蓋的語意概念，而非單純只考慮關鍵字本身。因此本研究基於現有運用在資訊檢索相關研究中的語意技術為基礎，從使用者提供之相關文件資訊中排除不含語意字詞並擷取具有高度語意關係字詞為查詢擴張字詞來源，試圖找出查詢和相關文件字詞間可利用的語意關係，並透過實驗證明語意應用方法可以和Rocchio演算法達到不分軒輊，甚至於更佳的效果。

摘要(英)

In previous vector space model and relevance feedback studies, the result is determined by the frequency of the terms in the list of relevant documents after users input their queries into the information retrieval system. One of the most popular methods is Rocchio′s query expansion algorithm, which has good performance and is often used in many cases. However, it has been highly focused in researches whether there are better methods to choosing relevant words and filtering out irrelevant words. In recent years, the semantic analysis techniques are developed, which emphasizes the meaning of terms rather than just the terms themselves. Many search engines have adopted these techniques to judge the result of relevant feedback. In this research, we try to find the usable meanings between the query and relevant words. The performance of the methods based on semantic analysis techniques in this research has been evaluated in experiments and proved to work as good as Rocchio’s algorithm, in some cases even better.

關鍵字(中)

★ 資訊檢索
★ 語意分析
★ 相關回饋
★ 查詢擴張

關鍵字(英)

★ Information Retrieval
★ Semantic Analysis
★ Relevance Feedback
★ Query Expansion

論文目次

中文摘要 iv
英文摘要 v
致謝 vi
目錄 vii
圖目錄 ix
表目錄 xi
ㄧ、緒論 1
1-1 研究背景與動機 1
1-2 研究目的 2
1-3 研究範圍與限制 2
1-4 論文架構 2
二、文獻探討 3
2-1 相關回饋 (Relevance Feedback) 3
2-1-1 相關回饋背景介紹與分類 3
2-1-2 向量空間模型 (Vector Space Model) 4
2-1-3 Rocchio演算法 (Rocchio Algorithm) 4
2-1-4相關回饋之相關研究整理 5
2-2 查詢擴張 (Query Expansion) 6
2-3 WorldNet 7
2-3-1 WordNet簡介 7
2-3-2 WordNet架構 8
2-3-3 WordNet語意相關程度計算 8
2-3-4 WordNet應用限制 9
2-3-5 WordNet應用之相關研究整理 10
2-4 小結 11
三、研究方法 12
3-1 系統架構 12
3-1-1 語意分析技術應用方法 13
3-1-2 文件重排序 14
3-2 應用方法設計 14
3-2-1 語意註解應用方法 14
3-2-2 語意距離應用方法 16
四、實驗設計 18
4-1實驗資料 18
4-2 實驗評估指標 21
4-3 實驗流程設計 23
4-3-1 實驗ㄧ流程設計 24
4-3-2 實驗二流程設計 25
4-4 實驗結果 26
4-4-1實驗1-1結果 26
4-4-2實驗1-2結果 30
4-4-3實驗2-1結果 35
4-4-4實驗2-2結果 38
4-5 實驗結果討論 42
五、結論 43
5-1 結論與貢獻 43
5-2 未來研究方向 43
參考文獻 44

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指導教授

周世傑(Shih-Chieh Chou)

審核日期

2014-7-7

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