561
个编辑
更改
→光谱上存在的径向体积中心
Bonacich showed that if association is defined in terms of walks, then a family of centralities can be defined based on the length of walk considered. Degree centrality counts walks of length one, while eigenvalue centrality counts walks of length infinity. Alternative definitions of association are also reasonable. Alpha centrality allows vertices to have an external source of influence. Estrada's subgraph centrality proposes only counting closed paths (triangles, squares, etc.).
Bonacich showed that if association is defined in terms of walks, then a family of centralities can be defined based on the length of walk considered. Degree centrality counts walks of length one, while eigenvalue centrality counts walks of length infinity. Alternative definitions of association are also reasonable. Alpha centrality allows vertices to have an external source of influence. Estrada's subgraph centrality proposes only counting closed paths (triangles, squares, etc.).
Bonacich 指出，如果联想是根据行走来定义的，那么可以根据考虑的行走长度来定义一个集中性家族。'''<font color="#ff8000"> 度集中度Degree centrality</font>'''计算长度为1的行走，'''<font color="#ff8000">特征值集中度Eigenvalue centrality </font>'''计算长度为无穷大的行走。关联的其他定义也是合理的。'''<font color="#ff8000"> 阿尔法中心性Alpha centrality</font>'''允许顶点有一个外部影响源。埃斯特拉达的'''<font color="#ff8000"> 子图中心性Subgraph centrality </font>'''提出只计算封闭路径(三角形、正方形等)。).
Bonacich 指出，如果联想是根据行走来定义的，那么可以根据考虑的行走长度来定义一个中心性家族。'''<font color="#ff8000"> 度中心性Degree centrality</font>'''计算长度为1的行走，'''<font color="#ff8000">特征值中心性Eigenvalue centrality </font>'''计算长度为无穷大的行走。关联的其他定义也是合理的。'''<font color="#ff8000"> 阿尔法中心性Alpha centrality</font>'''允许顶点有一个外部影响源。埃斯特拉达的'''<font color="#ff8000"> 子图中心性Subgraph centrality </font>'''提出只计算封闭路径(三角形、正方形等)。).
===Game-theoretic centrality===
===Game-theoretic centrality===
=='''<font color="#ff8000"> 博弈论中心性Game-theoretic centrality</font>'''==
=='''<font color="#ff8000"> 博弈论中心性Game-theoretic centrality</font>'''==
The common feature of most of the aforementioned standard measures is that they assess the importance of a node by focusing only on the role that a node plays by itself. However, in many applications such an approach is inadequate because of synergies that may occur
The common feature of most of the aforementioned standard measures is that they assess the importance of a node by focusing only on the role that a node plays by itself. However, in many applications such an approach is inadequate because of synergies that may occur