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Currently, community detection has led to a huge interest in data analysis on real-world networks. However, the high computationally demanding of most community detection algorithms limits their applications. In this paper, we propose a heuristic algorithm to extract the community structure in large networks based on local community attractive force optimization whose time complexity is near linear...
Graph theory is the theoretical fundamental of network technologies. This paper reports an investigation of stability issues of the network technologies based on the graph theory. It also presents solutions of the geodetic number of graph Cm times Cn. There are many parameters which can measure to some extent the robustness of an interconnection network with respect to link failures, such as domination...
Graph theory is the fundamental basis of the neural networks. This paper reports the investigation work of the relationships between artificial neural networks and graph theory, and presents the analysis of the specific issues relating to the change of the geodetic number due to operations on the graphs. Recent research work on the geodetic number of graphs has been found in the literature. Determining...
Efficient enumeration of all maximal cliques in a given graph has many applications in graph theory, data mining and bio informatics. However, the exponentially increasing computation time of this problem confines the scale of the graph. Meanwhile, recent researches show that many networks in our world are complex networks involving massive data. To solve the maximal clique problem in the real-world...
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