本研究利用現有的網際網路資源，有計畫的對不同資料來源進行抓取、分析與融合，以建構出所有大專院學教師的社會網絡，並以圖形化及數值分析的方式，呈現教師之社會網絡特性。並以萃取出之各類人際關係型態，作為分析之單元，依照使用者輸入權重之高低，動態計算出兩教師或研究人才間之最短關係路徑，與教師之自我中心網絡，實作出知識地圖的概念。本研究更提出以師生論文指導關係為連結的分析方式，結合多階層遞迴延伸之概念，建構出教師指導關係之家族樹，並以總圖與非樹葉簡圖兩種不同的觀點，呈現家族樹關係圖之資訊，再應用圖形理論中樹的特徵分析方式，結合現實社會中的人際關係網路觀點，對各項特性進行統計與分析，並以數值的方式，呈現其社會網絡結構特徵•
本研究最後結合社會網絡與知識地圖之概念，實作出ANIWEB系統，並以網路服務的方式提供使用者進行教師社會網路相關資訊的查詢。提供查詢的內容可分為教師或研究人才的個人化資訊，及社會網絡資訊等兩種類型，其中個人化資訊提供的是個人基本資料與學經歷、研究專長與國家科學委員會研究計畫資料等，而社會網絡資訊查詢則涵蓋多階層指導關係、共同指導關係、師承溯源、自我中心網絡，與兩教師間最短關係路徑搜尋等。使用者可依照目的與需求之不同，進行各類查詢，如：由研究主題尋找專家，再依情境調整關係權重，進行最短關係路徑搜尋，由系統建議接觸此研究人才的最佳管道；或是對特定對象，查詢其所有個人化資訊，並可由師承溯源發現其師承何人，由共同指導關係搜尋發現其論文協同指導之合作對象，或由家族樹關係圖與家族樹數值分析掌握其學術偏向、家族樹大小等特性；自我中心網絡則可以單一對象為中心，依照使用者調整之關係權重，搜尋出與此中心節點關係最密切之教師或研究人才。

This research is aimed to build a social network system for college teachers by retrieving different data sources available on the Internet, the characteristics of the constructed social network are represented in graphic and numeric modes. By applying relationships maintained in the social network, we can find the shortest path between any two researchers or the ego-center social network of any individual teacher according to the input parameters given by a query user.. That is to say we have realized the knowledge map concept for college teachers.
In this research, we focus on searching the advisory relationships between advisors and students. . Because after a Ph.D. student graduated, he/she could be an advisor guiding other students, by applying recursion of advisory relationships ， we can construct a multi-level hierarchy of family-tree for a given advisor and the family-tree can be viewed as a whole family-tree and just those non-leaf nodes. We also analyzed some interesting characteristics of the created family-tree， compared with the human relationships in our real society to evaluate and explain some phenomena happened in our academic society.
Furthermore, we combine two information of social network and knowledge map for developing the ANIWEB system, providing web-based query functions for users to search teachers’ social network. Two types of query can be applied, one is searching for teacher’s personal information, such as biography, educational background, specialty and NSC projects; the other is searching for social network information about an interested teacher, such as multi-level advisory relationship, co-advisory relationship, ego-center social network and the shortest path between any two teachers.
Users can apply different search patterns for their different needs. For example, a user can first search for those teachers with an expertise of a given research topics, then search for the shortest path from the social network to find out the expert he/she could get in touch.

目錄 II
圖目錄 V
表目錄 VII
公式目錄 VII
第1章 緒論 1
1.1 研究背景與動機 2
1.2 研究目的 4
1.3 研究範圍 6
1.4 論文架構 6
第2章 文獻探討 8
2.1 社會網絡分析 8
2.1.1 社會網絡分析的單元 9
2.1.2 社會網絡的結構特性 12
2.1.3 社會網絡分析的種類 13
2.1.4 社會網絡分析資料蒐集方法 15
2.2 圖形理論及樹狀結構表示法 18
2.2.1 圖形理論之分析與表示方法 18
2.2.2 樹狀結構表示法 21
2.2.3 最短路徑演算法 23
2.3 特徵詞彙篩選特徵詞彙篩選 24
2.4 代理人理論與技術 25
第3章 系統分析與設計 28
3.1 資料蒐集方法 28
3.2 系統流程與架構 30
3.2.1 資訊的蒐集、抓取與修正 32
3.2.2 資料整合、資訊萃取與內容分析 34
3.2.3 關係資訊與個人化資訊的搜尋與計算 35
3.3 多階層指導關係之分析與呈現 38
3.3.1 多層關係之蒐集、確認與儲存 39
3.3.2 建立家族樹關係圖之總圖與非樹葉簡圖 39
3.3.3 各項相關分數計算 41
3.4 師承溯源與共同指導關係 43
3.4.1 師承溯源 43
3.4.2 共同指導關係 44
3.5 自我中心社會網絡與最短關係路徑搜尋 45
3.5.1 自我中心社會網絡 45
3.5.2 最短關係路徑搜尋 46
第4章 系統實作 48
4.1 個人身份辨識系統 48
4.1.1 個人身份辨識 49
4.1.2 專家詳細資訊萃取 52
4.1.3 關係資訊萃取 53
4.2 個人資訊萃取系統 56
4.3 人際關係萃取系統 57
4.3.1 師生指導關係搜尋模組 58
4.3.2 自我中心網絡處理模組 62
4.3.3 最短關係路徑搜尋模組 64
第5章 實例分析 69
5.1 教師個人化資訊 69
5.1.1 個人基本資料與學經歷 70
5.1.2 專長資訊 72
5.1.3 國家科學委員會研究計畫 74
5.2 社會網絡資訊 75
5.2.1 多階層指導關係 76
5.2.2 共同指導關係與師承溯源 82
5.2.3 自我中心網絡分析 86
5.2.4 最短關係路徑搜尋 92
5.3 查詢次數統計排行與快速整合式查詢 96
5.3.1 查詢次數統計排行 96
5.3.2 快速整合式查詢 97
第6章 結論 99
6.1 實務上的意涵 100
6.2 研究上的意涵 102
6.3 研究成果 104
6.4 研究限制 105
6.5 未來研究議題 105
參考文獻 110
中文參考文獻 110
英文參考文獻 111
附錄一：Dijkstra’s　演算法 116

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