於本論文中我們提出三種估算網路（圖型）特性的估算方法，分別用來估算：(1)平均連結數，(2)節點涵蓋時間，以及(3)群聚係數。我們的關鍵想法在於藉由一個簡單隨機漫步走過少量的節點來估算整體網路的特性。在此論文裡，簡單隨機漫步的停止時機設定在當簡單隨機漫步走過目標比例的節點時，隨機漫步即會停止並利用估算演算法進行估算。為了要估算一個網路的平均連結數，我們從簡單隨機漫步測量取得的多餘連結分佈來推導出一個估算演算法。為了要估算一個圖型中少量節點的節點涵蓋時間，我們從一個同樣大小的完整連結圖型來推導出一個估算演算法，其中完整連結圖型的節點涵蓋時間可從彩券收集者問題來近似計算取得。為了要估算一個網路的群聚係數，我們直接從群聚係數的定義提出一個估算方法，其中群聚係數的定義為：網路中一個節點的兩個相連鄰近節點也彼此互相連結的機率。在論文的最後，我們將上述的三種網路特性估算方法分別應用在兩種電腦產生的隨機圖型（ＥＲ模型和Ｃｏｎｆｉｇｕｒａｔｉｏｎ模型）以及一個真實世界的Ｆａｃｅｂｏｏｋ紐奧良地區網路，並展示其模擬結果。

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