计算机工程
計算機工程
계산궤공정
COMPUTER ENGINEERING
2014年
9期
124-129,142
,共7页
田雪颖%刘衍珩%孙鑫%王亚洲%林佳佳
田雪穎%劉衍珩%孫鑫%王亞洲%林佳佳
전설영%류연형%손흠%왕아주%림가가
社交网络%网络拓扑%随机游走%PageRank算法%过渡概率%仿真模型
社交網絡%網絡拓撲%隨機遊走%PageRank算法%過渡概率%倣真模型
사교망락%망락탁복%수궤유주%PageRank산법%과도개솔%방진모형
social network%network topology%random walking%PageRank algorithm%transition probability%simulation model
针对移动社交网络的动态性、用户不同重要性和信息交互有向性,基于4种初始网络提出能准确描述移动社交网络结构的拓扑模型。采用随机游走理论和改进的PageRank算法,引入过渡概率使每两时步之间的网络拓扑结构相互联系。通过PageRank算法得到节点的势,进而求出概率过渡矩阵,利用随机游走理论由上一时步边存在概率矩阵和概率过渡矩阵得到当前时步边存在概率矩阵,每一时步动态地增加一个节点并检验是否有离开的节点。仿真结果显示,该模型在4种初始网络下得到的网络拓扑结构,入度、出度、势分布以及度-势相关性均具有明显幂律特性,表明随机游走理论和改进的PageRank算法能较准确描述移动社交网络,具有一定的实践意义。
針對移動社交網絡的動態性、用戶不同重要性和信息交互有嚮性,基于4種初始網絡提齣能準確描述移動社交網絡結構的拓撲模型。採用隨機遊走理論和改進的PageRank算法,引入過渡概率使每兩時步之間的網絡拓撲結構相互聯繫。通過PageRank算法得到節點的勢,進而求齣概率過渡矩陣,利用隨機遊走理論由上一時步邊存在概率矩陣和概率過渡矩陣得到噹前時步邊存在概率矩陣,每一時步動態地增加一箇節點併檢驗是否有離開的節點。倣真結果顯示,該模型在4種初始網絡下得到的網絡拓撲結構,入度、齣度、勢分佈以及度-勢相關性均具有明顯冪律特性,錶明隨機遊走理論和改進的PageRank算法能較準確描述移動社交網絡,具有一定的實踐意義。
침대이동사교망락적동태성、용호불동중요성화신식교호유향성,기우4충초시망락제출능준학묘술이동사교망락결구적탁복모형。채용수궤유주이론화개진적PageRank산법,인입과도개솔사매량시보지간적망락탁복결구상호련계。통과PageRank산법득도절점적세,진이구출개솔과도구진,이용수궤유주이론유상일시보변존재개솔구진화개솔과도구진득도당전시보변존재개솔구진,매일시보동태지증가일개절점병검험시부유리개적절점。방진결과현시,해모형재4충초시망락하득도적망락탁복결구,입도、출도、세분포이급도-세상관성균구유명현멱률특성,표명수궤유주이론화개진적PageRank산법능교준학묘술이동사교망락,구유일정적실천의의。
A topological model that can describe the mobile social network accurately is proposed based on four initial networks considering the dynamic of social network, the different importance of users and the direction of information interaction. Random walking theory and improved PageRank algorithm are adopted,and transition probability is introduced to associate the network topological structure between two time-steps. Firstly, PageRank algorithm is used to obtain the strength of the nodes in order to get the probability transition matrix. Then random walking theory is used to get the current time-step edge existence probability matrix based on the last time-step edge existence probability matrix and the probability transition matrix. During each time-step,a node is added and it is checked if there is any departure node. Finally,simulation model is used to simulate the four initial networks in in-degree,out-degree,strength distribution and the correlation between degree and strength. The results indicate that the four initial networks’ in-degree,out-degree,strength distribution and the correlation between degree and strength show obvious power-law character. It shows that the random walking theory and improved PageRank algorithm can describe the mobile social network better,which is of certain practical significance.