博文
一篇好文章的好
||||
以下英文摘自Emergence of Scaling in Random Networks, By Albert Barabasi and Reka Albert
中文为我做出的解释
The difficulty of describing these systems lies partly in their topology: Many of them form rather complex networks whose vertices are the elements of the system and whose edges represent the interactions between them.指出网络拓扑中的节点与现实网络的对应关系。节点就是系统中的元素，边则相当于是之间的相互关系。
For example, living systems form a huge genetic network whose vertices are proteins and genes, the chemical interactions between them representing edges. At a different organizational level, a large network is formed by the nervous system, whose vertices are the nerve cells, connected by axons. But equally complex networks occur in social science, where vertices are individuals or organizations and the edges are the social interactions between them, or in the World Wide Web(WWW), whose vertices are HTML documents connected by links pointing from one page to another. 举出了几个例子，来分别进行对应。生命系统中的蛋白质和基因相当于节点，化学关系为边。神经系统，节点为神经细胞，由神经细胞的轴突进行连接。社会网络中，节点为个人或组织，边为相互之间的关系，三维网中，HTML文档相当于节点，网页之间的相互link相当于边。
文章的好还好在，不光是将网络拓扑结构中的两个基本概念（节点和边）与实际进行了联系，而且还进一步用这些实例，来解释了，为什么后来加上去的连接（link）更倾向于与本来连接度（connectivity）较高的节点进行相连。
most real networks exhibit preferential connectivity. For example, a new actor is most likely to be cast in a supporting role with more established and better-known actors. Consequently, the probability that a new actor will be cast with an established one is much higher than that the new actor will be cast with other less-known actors. Similarly, a newly created Web page will be more likely to include links to well-know popular documents with already-high connectivity, and a new manuscript is more likely to cite a well-known and thum much-cited paper than its less-cited and consequently less-known peer. These examples indicate that the probability with which a new vertex connects to the existing vertices is not uniform; there is a higher probability that will be linked to a vertex that already has a large number of connections.
演员更希望与比较有名的演员合作。那么，新演员就有更高的概率与比较有名的演员建立连系。新的网页也更愿意与连接度较高的网页进行相连。写文章的时候更愿意引用那些被很多人引用的文章（因为被很多人引用过说明，文章的质量比较高）。这被称作是preferential attachment
https://m.sciencenet.cn/blog-264887-239943.html
上一篇：算法研究的Philosophy
下一篇：一篇好学术论文
中文为我做出的解释
The difficulty of describing these systems lies partly in their topology: Many of them form rather complex networks whose vertices are the elements of the system and whose edges represent the interactions between them.指出网络拓扑中的节点与现实网络的对应关系。节点就是系统中的元素，边则相当于是之间的相互关系。
For example, living systems form a huge genetic network whose vertices are proteins and genes, the chemical interactions between them representing edges. At a different organizational level, a large network is formed by the nervous system, whose vertices are the nerve cells, connected by axons. But equally complex networks occur in social science, where vertices are individuals or organizations and the edges are the social interactions between them, or in the World Wide Web(WWW), whose vertices are HTML documents connected by links pointing from one page to another. 举出了几个例子，来分别进行对应。生命系统中的蛋白质和基因相当于节点，化学关系为边。神经系统，节点为神经细胞，由神经细胞的轴突进行连接。社会网络中，节点为个人或组织，边为相互之间的关系，三维网中，HTML文档相当于节点，网页之间的相互link相当于边。
文章的好还好在，不光是将网络拓扑结构中的两个基本概念（节点和边）与实际进行了联系，而且还进一步用这些实例，来解释了，为什么后来加上去的连接（link）更倾向于与本来连接度（connectivity）较高的节点进行相连。
most real networks exhibit preferential connectivity. For example, a new actor is most likely to be cast in a supporting role with more established and better-known actors. Consequently, the probability that a new actor will be cast with an established one is much higher than that the new actor will be cast with other less-known actors. Similarly, a newly created Web page will be more likely to include links to well-know popular documents with already-high connectivity, and a new manuscript is more likely to cite a well-known and thum much-cited paper than its less-cited and consequently less-known peer. These examples indicate that the probability with which a new vertex connects to the existing vertices is not uniform; there is a higher probability that will be linked to a vertex that already has a large number of connections.
演员更希望与比较有名的演员合作。那么，新演员就有更高的概率与比较有名的演员建立连系。新的网页也更愿意与连接度较高的网页进行相连。写文章的时候更愿意引用那些被很多人引用的文章（因为被很多人引用过说明，文章的质量比较高）。这被称作是preferential attachment
https://m.sciencenet.cn/blog-264887-239943.html
上一篇：算法研究的Philosophy
下一篇：一篇好学术论文
