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网络的结构信息内容:基于局部顶点泛函的图熵

Structural information content of networks: graph entropy based on local vertex functionals.

作者信息

Dehmer Matthias, Emmert-Streib Frank

机构信息

Institute of Discrete Mathematics and Geometry, Vienna University of Technology, TU Vienna, Wiedner Hauptstrasse 8-10, A-1040 Vienna, Austria.

出版信息

Comput Biol Chem. 2008 Apr;32(2):131-8. doi: 10.1016/j.compbiolchem.2007.09.007. Epub 2007 Sep 29.

Abstract

In this paper we define the structural information content of graphs as their corresponding graph entropy. This definition is based on local vertex functionals obtained by calculating j-spheres via the algorithm of Dijkstra. We prove that the graph entropy and, hence, the local vertex functionals can be computed with polynomial time complexity enabling the application of our measure for large graphs. In this paper we present numerical results for the graph entropy of chemical graphs and discuss resulting properties.

摘要

在本文中,我们将图的结构信息内容定义为其相应的图熵。该定义基于通过迪杰斯特拉算法计算j - 球体得到的局部顶点泛函。我们证明了图熵以及局部顶点泛函可以在多项式时间复杂度内计算,这使得我们的度量能够应用于大型图。在本文中,我们给出了化学图的图熵的数值结果并讨论了由此产生的性质。

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