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第18行：
第18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27行：
第26行： − “重要性”这个词有许多含义，导致了许多不同的中心性定义。分为两类。+
→中心性指数的定义与特性Definition and characterization of centrality indices
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="Bonacich1987">{{cite journal |last1= Bonacich |first1= Phillip|year= 1987 |title= Power and Centrality: A Family of Measures | journal=American Journal of Sociology |volume= 92|issue= 5|pages= 1170–1182|doi=10.1086/228631 |url= }}<!--|accessdate=July 11, 2014--></ref><ref name="Borgatti2005">{{cite journal |last1= Borgatti |first1= Stephen P.|year= 2005 |title= Centrality and Network Flow |journal=Social Networks |volume= 27|issue= |pages= 55–71|doi=10.1016/j.socnet.2004.11.008 |url= |citeseerx= 10.1.1.387.419}}<!--|accessdate= July 11, 2014--></ref><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 |author = 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.|title = Eigenvector centrality for characterization of protein allosteric pathways|journal = Proceedings of the National Academy of Sciences|volume = 115|number = 52|pages = E12201–E12208|year = 2018|doi = 10.1073/pnas.1810452115|pmid = 30530700|pmc = 6310864}}</ref>
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="Bonacich1987">{{cite journal |last1= Bonacich |first1= Phillip|year= 1987 |title= Power and Centrality: A Family of Measures | journal=American Journal of Sociology |volume= 92|issue= 5|pages= 1170–1182|doi=10.1086/228631 |url= }}<!--|accessdate=July 11, 2014--></ref><ref name="Borgatti2005">{{cite journal |last1= Borgatti |first1= Stephen P.|year= 2005 |title= Centrality and Network Flow |journal=Social Networks |volume= 27|issue= |pages= 55–71|doi=10.1016/j.socnet.2004.11.008 |url= |citeseerx= 10.1.1.387.419}}<!--|accessdate= July 11, 2014--></ref><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 |author = 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.|title = Eigenvector centrality for characterization of protein allosteric pathways|journal = Proceedings of the National Academy of Sciences|volume = 115|number = 52|pages = E12201–E12208|year = 2018|doi = 10.1073/pnas.1810452115|pmid = 30530700|pmc = 6310864}}</ref>
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="Bonacich1987">{{cite journal |last1= Bonacich |first1= Phillip|year= 1987 |title= Power and Centrality: A Family of Measures | journal=American Journal of Sociology |volume= 92|issue= 5|pages= 1170–1182|doi=10.1086/228631 |url= }}<!--|accessdate=July 11, 2014--></ref><ref name="Borgatti2005">{{cite journal |last1= Borgatti |first1= Stephen P.|year= 2005 |title= Centrality and Network Flow |journal=Social Networks |volume= 27|issue= |pages= 55–71|doi=10.1016/j.socnet.2004.11.008 |url= |citeseerx= 10.1.1.387.419}}<!--|accessdate= July 11, 2014--></ref><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 |author = 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.|title = Eigenvector centrality for characterization of protein allosteric pathways|journal = Proceedings of the National Academy of Sciences|volume = 115|number = 52|pages = E12201–E12208|year = 2018|doi = 10.1073/pnas.1810452115|pmid = 30530700|pmc = 6310864}}</ref>
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.
'''<font color="#ff8000">中心性指数 centrality indices</font>'''旨在探寻如何描绘重要节点这一问题。这一问题的答案通常实值函数的形式给出，可根据函数值将图中各节点进行排序，进而确定最为重要的节点。<ref name="Bonacich1987">{{cite journal |last1= Bonacich |first1= Phillip|year= 1987 |title= Power and Centrality: A Family of Measures | journal=American Journal of Sociology |volume= 92|issue= 5|pages= 1170–1182|doi=10.1086/228631 |url= }}<!--|accessdate=July 11, 2014--></ref><ref name="Borgatti2005">{{cite journal |last1= Borgatti |first1= Stephen P.|year= 2005 |title= Centrality and Network Flow |journal=Social Networks |volume= 27|issue= |pages= 55–71|doi=10.1016/j.socnet.2004.11.008 |url= |citeseerx= 10.1.1.387.419}}<!--|accessdate= July 11, 2014--></ref><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 |author = 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.|title = Eigenvector centrality for characterization of protein allosteric pathways|journal = Proceedings of the National Academy of Sciences|volume = 115|number = 52|pages = E12201–E12208|year = 2018|doi = 10.1073/pnas.1810452115|pmid = 30530700|pmc = 6310864}}</ref>
The word "importance" has a wide number of meanings, leading to many different definitions of centrality. Two categorization schemes have been proposed.
The word "importance" has a wide number of meanings, leading to many different definitions of centrality. Two categorization schemes have been proposed.
The word "importance" has a wide number of meanings, leading to many different definitions of centrality. Two categorization schemes have been proposed.
The word "importance" has a wide number of meanings, leading to many different definitions of centrality. Two categorization schemes have been proposed.
“重要性”的含义十分广泛，因此导致了许多不同的中心性定义方式。这些不同的定义方式大致可分为两类。
"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.<ref name=Borgatti2005/> "Importance" can alternatively be conceived as involvement in the cohesiveness of the network. This allows centralities to be classified based on how they measure cohesiveness.<ref name="Borgatti2006">{{cite journal |last1= Borgatti |first1= Stephen P.|last2= Everett |first2= Martin G.|year= 2006 |title= A Graph-Theoretic Perspective on Centrality |journal=Social Networks |volume= 28|issue= 4|pages= 466–484|doi=10.1016/j.socnet.2005.11.005 |url= }}<!--|accessdate= July 11, 2014--></ref> 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.<ref name=Borgatti2005/>
"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.<ref name=Borgatti2005/> "Importance" can alternatively be conceived as involvement in the cohesiveness of the network. This allows centralities to be classified based on how they measure cohesiveness.<ref name="Borgatti2006">{{cite journal |last1= Borgatti |first1= Stephen P.|last2= Everett |first2= Martin G.|year= 2006 |title= A Graph-Theoretic Perspective on Centrality |journal=Social Networks |volume= 28|issue= 4|pages= 466–484|doi=10.1016/j.socnet.2005.11.005 |url= }}<!--|accessdate= July 11, 2014--></ref> 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.<ref name=Borgatti2005/>