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第30行：
第30行： − ‘’‘<font color="#ff8000">中心性指数Centrality indices </font>'''是对“重要顶点的特征是什么”这一问题的回答，答案以图顶点的实值函数的方式给出，在这些顶点上的取值的排序标识出最重要的节点。+ 第106行：
第106行： − “重要性”可以被认为与一种跨网络的流动或传输有关。这允许根据它们认为重要的流类型对集中性进行分类。这两种方法都将集中性划分为不同的类别。进一步的推论是，适用于一个类别的中心性在（推广）应用于另一个类别时往往会“出错”。+ 第114行：
第114行： − 当中心性按照它们对内聚性的趋近程度来分类时，很明显，大多数中心性都集中在一个类别中。从一个给定顶点开始对步数计数，不同之处只在于行走的定义和计数方式。对该组描述的约束限制，从位置中心（度中心度）到单元域（特征中心度），观察到许多中心性都有这种相似关系，这也许可以解释这些指数之间的高阶相关性。+
→中心性指标的定义与特性
Centrality indices are answers to the question "What characterizes an important vertex?" The answer is given in terms of a real-valued function on the vertices of a graph, where the values produced are expected to provide a ranking which identifies the most important nodes.<ref name="Christian F. A. Negre, Uriel N. Morzan, Heidi P. Hendrickson, Rhitankar Pal, George P. Lisi, J. Patrick Loria, Ivan Rivalta, Junming Ho, Victor S. Batista. 2018 E12201--E12208">{{cite journal |
Centrality indices are answers to the question "What characterizes an important vertex?" The answer is given in terms of a real-valued function on the vertices of a graph, where the values produced are expected to provide a ranking which identifies the most important nodes.<ref name="Christian F. A. Negre, Uriel N. Morzan, Heidi P. Hendrickson, Rhitankar Pal, George P. Lisi, J. Patrick Loria, Ivan Rivalta, Junming Ho, Victor S. Batista. 2018 E12201--E12208">{{cite journal |
'''<font color="#ff8000">中心性指数Centrality indices </font>'''是对“重要顶点的特征是什么”这一问题的回答，答案以图顶点的实值函数的方式给出，在这些顶点上的取值的排序标识出最重要的节点。
< ref name = “ Christian f. a. Negre，Uriel n. Morzan，Heidi p. Hendrickson，Rhitankar Pal，George p. Lisi，j. Patrick Loria，Ivan Rivalta，Junming Ho，Victor s. Batista。2018 E12201-- E12208” > { cite journal |
< ref name = “ Christian f. a. Negre，Uriel n. Morzan，Heidi p. Hendrickson，Rhitankar Pal，George p. Lisi，j. Patrick Loria，Ivan Rivalta，Junming Ho，Victor s. Batista。2018 E12201-- E12208” > { cite journal |
"Importance" can be conceived in relation to a type of flow or transfer across the network. This allows centralities to be classified by the type of flow they consider important. Both of these approaches divide centralities in distinct categories. A further conclusion is that a centrality which is appropriate for one category will often "get it wrong" when applied to a different category.
"Importance" can be conceived in relation to a type of flow or transfer across the network. This allows centralities to be classified by the type of flow they consider important. Both of these approaches divide centralities in distinct categories. A further conclusion is that a centrality which is appropriate for one category will often "get it wrong" when applied to a different category.
“重要性”可以被认为与一种跨网络的流动或传输有关。这允许根据它们认为重要的流类型对中心性进行分类。这两种方法都将中心性划分为不同的类别。进一步的推论是，适用于一个类别的中心性在（推广）应用于另一个类别时往往会“出错”。
When centralities are categorized by their approach to cohesiveness, it becomes apparent that the majority of centralities inhabit one category. The count of the number of walks starting from a given vertex differs only in how walks are defined and counted. Restricting consideration to this group allows for a soft characterization which places centralities on a spectrum from walks of length one (degree centrality) to infinite walks (eigenvalue centrality). The observation that many centralities share this familial relationships perhaps explains the high rank correlations between these indices.
When centralities are categorized by their approach to cohesiveness, it becomes apparent that the majority of centralities inhabit one category. The count of the number of walks starting from a given vertex differs only in how walks are defined and counted. Restricting consideration to this group allows for a soft characterization which places centralities on a spectrum from walks of length one (degree centrality) to infinite walks (eigenvalue centrality). The observation that many centralities share this familial relationships perhaps explains the high rank correlations between these indices.
当中心性按照它们对'''<font color="#ff8000"> 内聚性Cohesiveness</font>'''的趋近程度来分类时，很明显，大多数中心性都集中在一个类别中。从一个给定顶点开始对步数计数，不同之处只在于行走的定义和计数方式。对该组描述的约束限制，从位置中心（度中心度）到单元域（特征中心度），观察到许多中心性都有这种相似关系，这也许可以解释这些指数之间的高阶相关性。
===Characterization by network flows==
===Characterization by network flows==