博碩士論文 105423041 詳細資訊




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姓名 孫智梁(Zhi-Liang Sun)  查詢紙本館藏   畢業系所 資訊管理學系
論文名稱 利用語意分析於相關回饋以進行查詢擴展之方法
(The application of semantic analysis in relevance feedback for query expansion)
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摘要(中) 現今我們處於資訊爆炸的時代,在面臨龐大資料量時,如何有效率地獲取所需資訊是一個非常重要的課題,而資訊檢索 (Information Retrieval) 系統也就成為人們在篩選資料時最常用的工具之一。在相關回饋 (Relevance Feedback) 領域中,Rocchio演算法最廣為人知,該演算法藉由分析相關文件字詞及非相關文件字詞出現頻率,來產生新的查詢字詞,並加入到查詢擴展 (Query Expansion) 集合中,不過Rocchio僅以頻率之角度判斷,並未考量字詞間其他可以利用的資訊。近年來陸續也有語意搜索的研究被提出,概念為發掘字詞間隱含的語意關係,因此,本研究以使用者的原始查詢和查詢結果作為基礎,主要利用神經網路模型Word2Vec來分析原始查詢以及相關回饋中字詞間的語意資訊,並結合共現性分析,萃取出適合的相關字詞來擴展原始查詢字詞集合,使查詢關鍵字能夠更貼近使用者需求。最後透過實驗證明,本研究所提出之方法相較於其他方法能有較佳的檢索效果。
摘要(英) In an era of information explosion, to obtain the information efficiently is a very important issue when faced with huge data volume, and the information retrieval system has become one of the most commonly used tools. In the field of relevance feedback, Rocchio’s query expansion is a well-known method. The algorithm generates new query terms by analyzing the frequency of terms which residing in relevance documents and non-relevance documents. However, Rocchio’s method only focuses on term frequency and ignores information between terms. In recent years, the idea of semantic search is getting more and more popular. Therefore, based on the user′s original query and search results, our research uses Word2Vec which is a neural network model to analyze the semantic information between the original query and the relevance feedback, and combine the co-occurrence analysis to extract the appropriate query expansion terms. The results of experiments verify that the proposed method is effective in document retrieval.
關鍵字(中) ★ 資訊檢索
★ 相關回饋
★ 查詢擴展
★ 語意分析
★ Word2Vec
關鍵字(英) ★ Information Retrieval
★ Relevance Feedback
★ Query Expansion
★ Semantic Analysis
★ Word2Vec
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 研究範圍及限制 2
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) 9
2-3 正規化Google距離 (Normalized Google Distance) 10
2-4 語詞資訊應用方法 11
2-5 Word2Vec 12
三、 研究方法 15
3-1 系統架構 15
3-2 方法設計 16
3-2-1原始查詢結果處理 17
3-2-2相關字詞之間的語意資訊處理 17
3-2-3原始查詢字詞語意資訊處理 18
3-2-4相關字詞之間的共現分析處理 20
四、 實驗設計 22
4-1 實驗資料 22
4-2 實驗評估指標 26
4-3 實驗流程 29
4-3-1 實驗一 30
4-3-2 實驗二 31
4-4 實驗結果 32
4-4-1 實驗一結果 32
4-4-2 實驗二結果 39
4-5 實驗結果討論 47
五、 結論 50
5-1 結論與貢獻 50
5-2 未來研究方向 51
參考文獻 52
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指導教授 周世傑(Shih-Chieh Chou) 審核日期 2018-7-30
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