應用查詢擴展之字詞語意資訊於文件重排序之方法

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姓名

蔡啓詳(Ci-Siang Cai) 查詢紙本館藏

畢業系所

資訊管理學系

論文名稱

應用查詢擴展之字詞語意資訊於文件重排序之方法
(The application of the semantic information of terms residing in query expansion for document re-ranking)

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摘要(中)

在相關回饋的領域當中，Rocchio演算法因容易實作且有一定的效能水準，在查詢擴展的研究中被廣為使用與研究，而該演算法依據相關文件詞頻及非相關文件詞頻之資訊，藉此產生新的查詢擴展字詞，並進行再次檢索。然而在進行再次檢索時，查詢擴展當中可用的字詞資訊並不會被使用於檢索的過程當中，因此查詢擴展字詞之間是否存在其他可以加以利用的資訊並應用於檢索當中，仍然是個有趣的議題。近年來，語意搜索的研究陸續被提出，主要考量到查詢字詞所涵蓋的語意概念，而非單純使用查詢字詞本身。因此，本研究基於現有的自然語言相關研究，運用WordNet之字詞語意資訊，計算查詢擴展字詞間之語意相似度，接著透過分群萃取出查詢擴展之概念資訊，依據本研究提出之方法計算出文件與查詢擴展之概念匹配程度，並將之使用於修正原始查詢擴展之排序。最後透過實驗證明，本研究所提出之方法與原始查詢擴展之效能相比之下，皆有更好的檢索效果。

摘要(英)

In the field of relevance feedback, Rocchio’s query expansion method is simple and effective. It has been widely used in information retrieval. Rocchio’s algorithm produces query expansion according to term frequency in the feedback documents provided by the user and uses it to retrieve documents. Although Rocchio’s method are effective, the terms’ information such as semantics are not utilized in the retrieval process. This study aims to analyze the terms’ information of query expansion and uses the terms’ information for document re-ranking. Recently, the idea of semantic search is getting more and more popular. It is concerned with the semantic meaning of the query terms. Based on NLP technique, this study utilizes WordNet which is a large lexical database of English to calculate semantic similarity between query terms and extract concepts of query expansion by using clustering algorithm. The proposed method calculates concept score between query expansion and each document, and uses the calculated concept score for document re-ranking. The results of experiments show that the proposed method of this study is effective in document retrieval.

關鍵字(中)

★ 資訊檢索
★ 相關回饋
★ 查詢擴展
★ WordNet
★ 文件重排序

關鍵字(英)

★ Information Retrieval
★ Relevance Feedback
★ Query Expansion
★ WordNet
★ Document Re-ranking

論文目次

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 2
1-4 論文架構 3
二、文獻探討 4
2-1 相關回饋 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 7
2-2-1 局部查詢擴展 (Local Query Expansion) 8
2-2-2 全域查詢擴展 (Global Query Expansion) 9
2-3 WordNet 9
2-4 分群相關研究 12
2-4-1 K-Means 12
2-4-2 Affinity Propagation 12
2-4-3 字詞語意分群 15
三、研究方法 17
3-1 系統架構 17
3-2 方法設計 18
3-2-1 原始查詢結果處理 18
3-2-2 查詢擴展字詞之語意分群處理 19
3-2-3 重排序處理 26
四、實驗設計 29
4-1 實驗資料 29
4-2 實驗評估指標 32
4-3 實驗參數設定 35
4-3-1 概念之數量設定 35
4-3-2 重排序演算法之參數設定 36
4-4 實驗流程 37
4-4-1 實驗一之流程 37
4-4-2 實驗二之流程 38
4-5 實驗結果 39
4-5-1 實驗一之結果 39
4-5-2 實驗二之結果 47
4-6 實驗結果討論 55
五、結論 56
5-1 結論與貢獻 56
5-2 未來研究方向 57
參考文獻 58

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指導教授

周世傑(Shih-Chieh Chou)

審核日期

2017-7-6

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