臺灣博碩士論文加值系統

資訊檢索 (Information Retrieval)系統在人們的生活中已經是一個不可或缺的重要工具，相關回饋 (Relevance Feedback)的領域中Rocchio演算法因實作簡單且具有一定的效能，所以經常被廣泛的使用與研究，其概念為分析相關回饋結果中字詞的重要程度，作為挑選查詢擴展 (Query Expansion)字詞之依據，使資訊檢索系統更貼近使用者的資訊需求，但是其僅單純著重於字詞的出現頻率作為文件相關與否的依據，沒有考慮到字詞之間是否存在其他可以善加利用的資訊，而且在真實世界中出現頻率最高的字詞不一定與使用者的資訊需求具有相關性。因此本研究運用相關回饋的概念，分析相關文件中字詞之間所隱含的語意關係與共現關係，萃取其中適合的相關字詞作為查詢擴展之字詞來源，目的在於使查詢關鍵字能更符合使用者之資訊需求，解決過往相關回饋僅考慮字詞出現頻率而忽略的語詞資訊，並透過實驗證明本研究所提出之方法與其他方法相比之下，皆能有不錯的檢索效果，達到提升文件檢索準確率之最終目的。

Information retrieval systems are an indispensable tool in people's lives. Rocchio’s query expansion method is simple and effective in the analyzing of the importance of terms residing in relevance feedback. However, in the make up of terms and its importance for query expansion, Rocchio’s method only focuses on term frequency and ignores other relationships between terms. Therefore, this study is aimed to develop a method in the utilization of the information of relevance feedback to analyze the semantic and co-occurrence relationships of terms in relevant documents to extract adequate relevant terms for query expansion. The results of experiments show that the proposed method of this study is effectiveness in document retrieval.

中文摘要 i
英文摘要 ii
誌謝 iii
目錄 iv
圖目錄 vi
表目錄 viii
一、 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 3
1-4 論文架構 3
二、 文獻探討 4
2-1 相關回饋 (Relevance Feedback) 4
2-1-1 相關回饋背景與應用 4
2-1-2 Rocchio演算法 6
2-2 查詢擴展 (Query Expansion) 8
2-2-1 局部查詢擴展 (Local Query Expansion) 9
2-2-2 全域查詢擴展 (Global Query Expansion) 10
2-3 WordNet 10
2-4 語意註解應用方法 13
2-5 正規化Google距離 (Normalized Google Distance, NGD) 15
三、 研究方法 17
3-1 系統架構 17
3-2 方法設計 18
四、 實驗設計 25
4-1 實驗資料 25
4-2 實驗評估指標 29
4-3 實驗之查詢主題設定 32
4-4 實驗流程 33
4-4-1 實驗一 34
4-4-2 實驗二 34
4-5 實驗結果 35
4-5-1 實驗一結果 35
4-5-2 實驗二結果 42
4-6 實驗結果討論 50
五、 結論 52
5-1 結論與貢獻 52
5-2 未來研究方向 53
參考文獻 54

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