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研究生:黃勝偉
研究生(外文):Sheng-Wei Huang
論文名稱:方向性鏈結分析技術之開發與應用
論文名稱(外文):Development and Application of a Directional Link Analysis Technique
指導教授:陳鴻文陳鴻文引用關係
指導教授(外文):Hown-Wen Chen
學位類別:碩士
校院名稱:大葉大學
系所名稱:資訊管理學系碩士班
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:2007
畢業學年度:95
語文別:中文
論文頁數:80
中文關鍵詞:圖形理論(graph theory)社會網絡分析(social network analysis)方向性鏈結分析(directional link analysis)安隆電子郵件分析(Enron corpus analysis)弱鏈結(weak tie)
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  • 收藏至我的研究室書目清單書目收藏:2
由於涉及隱私、商業機密與社會環境背景等的特性資料取得不易,研究學者一般僅能針對少量的資料,運用社會網絡分析工具及技術,探討個體間的關係、群體結構特性及其行為特徵等意涵。然而過去社會網絡分析,大多偏重於網絡中心成員的辨識,甚少著墨於子群組間交互影響與關係上,也無法分析出群體群組間相互的作用關係。因此本研究主要目標是從社會網絡的潛在結構中,發掘出其間子群組之間的動態關係。
本研究在測試資料集方面,是以安隆公司電子郵件資料集及實際被起訴名單,來進行所設計技術的說明及效能驗證。首先是以內文主題分類(McCallum et al., 2005)的觀念進行前置處理,再利用所提出之方向性鏈結分析技術DLA的作法,對元件間橋樑路徑進行適當分類;接著再藉由所提出之網絡結構差異性分析DNSA技術,進行雜訊節點的過濾,以期發掘出可能涉及詐欺的員工。實驗結果顯示在預測方面的平均準確率可達83.07%,而平均所需執行時間為1.47秒。所以在圖形資料的自動分析方面,可達到節省大量人力時間的支出,和免除主觀上人為的判斷的目的。
Traditional techniques of social network analysis mainly focused on identify the central members in a network, but rarely explored the interaction and relationships be-tween actors and sub-groups. A lot of information within a network is hence ignored. Therefore, a novel directional link analysis technique is proposed here. Instead, both dynamic and static relationships between actors and sub-groups will be investigated from the latent structure of a network.
Enron e-mail corpus and indictment name list were used to illustrate and demon-strate the proposed techniques. First, the e-mail contact networks were classified by the topics of e-mail contents between July and Nov. 2001 which were regarded as the pe-riod of Enron fraud crisis. Following that, strongly connected components, communi-cation bridges between components and other topological information of the e-mail networks were found by the proposed Directional Link Analysis (DLA). To identify the employee involving fraud within the node set found by DLA. The experimental results illustrated the effectiveness and efficiency of the proposed methods by the average de-tection rate and the average running time being 83.07% and 1.47 seconds, respectively. Therefore, DLA and DNSA are useful as novel tools of automatic link analysis because of their efficiency and objectiveness.
中文摘要 iii
英文摘要 v
誌謝辭 vii
內容目錄 viii
表目錄 x
圖目錄 xii
第一章 緒論 1
第一節 研究背景及動機 1
第二節 研究目的 3
第三節 研究範圍與限制 3
第四節 論文架構 4
第二章 文獻探討 6
第一節 鏈結分析的問題 6
第二節 圖形理論 13
第三節 社會網絡分析 17
第四節 安隆公司 23
第三章 研究方法與設計 31
第一節 研究方法與架構 31
第二節 方向性鏈結分析(Directional Link Analysis, DLA)   37
第三節 網絡結構差異分析(Differentiation of Network Structure Analysis, DNSA) 41
第四章 實驗與結果評估 50
第一節 開發工具與設計環境 50
第二節 實驗資料來源 50
第三節 實驗結果分析 54
第四節 結果評估比較 61
第五章 結論與未來研究方向 65
第一節 結論 66
第二節 後續研究發展建議 67
參考文獻 68
附錄A 81
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