在這個資訊爆炸的時代，網路使用者透過現今的資訊搜索功能，多半能迅速檢索到大量的相關資訊，但很可能因為精確度欠佳及各種影響檢索系統判別的因素之存在，而使得使用者經常檢索出過多的資訊，而這些資訊又往往與使用者的期待相距甚遠，雖然能夠在一時之間搜尋整理出大量的相關資訊，但卻無法精準地達到其資料搜尋應有的效率。本研究為了謀求這個問題的解決方法，是以『以關鍵字序列型樣探勘為基礎之文件檢索方法』研究的目的與主題。
    使用者經常性檢索出過多資訊的主要原因，多半是由於檢索系統對於關鍵字的斷句位置判斷錯誤，進而導致檢索系統最後檢索出錯誤的資訊。
    本研究方法首先利用以關鍵字輸入之先後順序作為篩選方式，減少與使用者輸入之關鍵字詞不契合的網站，再透過序列型樣探勘加強並且揣測使用者所需要的檔，並且根據此項結果，進行排序的計算，加速使用者在尋找檔時的便利性。實驗顯示，與目前大部分檢索網站所檢索出結果比較，本方法確實可以檢索出更精簡、更正確的資訊。

In this age of information explosion, internet users through today's information-search feature, most quickly retrieved a large number of relevant information, but in all probability due to the poor and various impacts retrieval system discrimination factors exist, making users usually retrieved too much information. This study to the problem, is to “Document retrieval based on mining keywords sequential patterns” to purpose and solve in the topic.
    This information is often related to a user's expectations far cry, although to be able to put together all of a sudden to search for a great deal of information, but it still cannot really reaches its data to search for the necessary efficiency.
    First, the study use keywords which user’s key in Successively select that not match the web site and decrease result. And using sequential patterns mining to strengthen and guess user what they want documents, according to this result to calculate the rank, speeding up looking for documents by user.The experiment shows, and most research sites the comparison is retrieved as a result, this method can be retrieved more simple and correct information.

第一章 前言 1
1.1 背景 1
1.2 研究動機 3
1.3 研究方法與步驟 5
1.4 論文內容大綱 6
第二章 文獻探討及相關研究 7
2.1 資訊檢索(Information retrieval) 7
2.1.1 布林函數模型(Boolean Model) 7
2.1.2 向量空間模型(Vector Space Model) 8
2.1.3 文件檢索(document retrieval) 11
2.2 現行的網頁排序所用的演算法 12
2.2.1 PageRank Algorithm 12
2.2.2 PageRank的優缺點 18
2.2.3 Timed PageRank演算法 18
2.3 資料探勘(data mining) 19
2.3.1 資料探勘 19
2.3.2 序列型樣探勘 22
第三章 以關鍵字序列型樣探勘為基礎之檔檢索方法 27
3.1 模型架構 27
3.2 資料預處理 29
3.3 依關鍵字順序篩選文件 30
3.4 序列型樣探勘 35
3.5 依Score值排序文件 39
3.6 選擇使用者需要的關鍵字 40
第四章 實驗結果 41
4.1 實驗資料來源 41
4.2 實驗流程 41
4.3 檢索的效能評估 52
4.4 實驗結果 54
第五章 結論與未來展望 55
5.1 結論 55
5.2 未來展望 55
參考文獻 57
附錄-英文論文 61

圖目錄
圖2-1 向量空間模型 8
圖2-2 資料探勘 20
圖3-1 本方法對使用者所輸入關鍵字進行文章搜尋的流程圖 28
圖3-2 篩選順序正確文件之流程圖 34
圖3-3 關鍵字序列型樣探勘流程圖 38

表目錄
表2-1 相似度計算公式比較 10
表4-1 資料預處理 41
表4-2 C1的部分資料，support count=15 44
表4-3 C2的部分資料，support count=6 45
表4-4 C3的資料 46
表4-5 部分文章之n, m, SL, Total.gaps和score值 47
表4-6 各文章優先值(Score)及序列長度 47
表4-7 查詢需求各階段的篩檢 52
表4-8 實驗結果 53

公式目錄
式（1） 39

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