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研究生:賴靜怡
研究生(外文):Ching-Yi Lai
論文名稱:自動建立Ontology應用於User Profile建立
論文名稱(外文):Automatically Constructing Ontology Applied to User Profile Creation
指導教授:林熙禎林熙禎引用關係
指導教授(外文):Shi-Jen Lin
學位類別:碩士
校院名稱:國立中央大學
系所名稱:資訊管理學系
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2013
畢業學年度:101
語文別:中文
論文頁數:69
中文關鍵詞:階層分群動態分群
外文關鍵詞:OntologyExplicit profileImplicit profile
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網路的發展使得資料量愈來愈龐大,使用者要從大量的資訊中找到目標是非常困難的,因此本研究利用自建的ontology架構來建立user profile ontology來幫助記錄使用者興趣。本研究主要分兩大部份:自動建立ontology與user profile建立。在自動建立ontology部份,過去大部份的ontology都由領域專家手動建立,非常耗時與維護更新不易,因此本研究提出使用動態文件階層分群來建立ontology架構,其中我們針對部份流程進行優化,改善其準確度與效能。User profile部份,本研究利用自建的ontology架構再加上使用者接觸過的文章與行為因子來建立explicit profile與implicit profile,並且此user profile可以表達使用者不同時期的興趣與達到使用者興趣的延伸,可以幫助使用者找到符合興趣的文章。
The development of Internet makes the amount of data get larger. It is very difficult for user to find the data they want among the huge amount of data. This study creates user profile ontology by using the self-built ontology to record user’s interest. This study consists of two parts: automatically constructing ontology and user profile creation. In the first part, most ontology was created manually by experts, it was not only time-consuming but also hard to maintain and update. Therefore, this study constructs ontology by dynamically hierarchical clustering on document, and we optimize parts of the process to improve the accuracy and performance. In the part of user profile creation, this study use the self-built ontology, the articles that user had read and behavioral factors to create explicit profile and implicit profile. And these user profiles represent the interests in the different periods or the extension of interests of user, it help user to find the article what they may have interest.

一、緒論 1
1-1 研究背景 1
1-2 研究動機 2
1-3 研究目的 3
1-4 研究方法 4
1-5 論文架構 5
二、文獻探討 6
2-1 文件特徵選取 6
2-1-1 NGD 6
2-1-2 K-core 8
2-2 自建搜尋引擎 9
2-3 文件分群 10
2-3-1 文件分群技術分類 10
2-3-2 文件分群應用-動態文件階層分群 12
2-4 使用者輪廓 15
2-4-1 顯性輪廓 17
2-4-2 隱性輪廓 17
2-5 本體論 18
三、研究方法與系統架構 20
3-1 系統架構 20
3-2 自動建立本體論 21
3-2-1 資料前處理 22
3-2-2 文件概念分群 22
3-2-3 建置分類學與文件階層分群 23
3-3使用者輪廓計算模組 24
3-3-1 顯性輪廓計算 24
3-3-2 隱性輪廓計算 28
3-4 使用者輪廓本體論 29
3-4-1 建立使用者輪廓本體論架構 30
3-4-2 更新使用者輪廓本體論 31
四、實驗結果與討論 33
4-1 資料集介紹 33
4-1-1 Reuters-21578 33
4-1-2 維基百科 34
4-2 評估方法 34
4-3 實驗環境 36
4-4 文件前處理實驗結果 36
4-5 文件概念分群實驗結果 38
4-6 Explicit profile實驗 39
4-6-1 α值參數調整實驗 39
4-6-2 Explicit profile 不同domain下實驗 40
4-6-3Explicit profile 同domain下實驗 42
4-6-4 Explicit profile 於同domain與不同domain下建立之比較 43
4-7 Implicit profile實驗 43
4-7-1 Implicit profile實驗-Technology and applied sciences 44
4-7-2 Implicit profile實驗- Geography and places 45
4-7-3 Implicit profile於不同domain比較 45
4-8 Explicit profile 時間性實驗 46
4-8-1 UIA之φ參數調整 46
4-8-2 EI門檻值調整 47
4-8-3 Explicit profile時間性實驗 48
五、結論與未來研究方向 51
5-1 結論 51
5-2未來研究方向 52
5-3管理意涵 54
參考文獻 55

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