Complex Network Search Strategy Combined With Max Degree And Min Clustering Coefficient

Search problem in the complex network involved in finding the specified file or data and determining the shortest path between nodes, has important practical significance and research value. Complex network search strategy, adopted the local search methods, is described as a message transfer process. Its performance will directly affect the ability to search quickly and efficiently and the cost can be accepted. Real complex network generally has a variety of topological characteristics. This paper takes into account the scale-free and small world properties, conducted in-depth analysis, research and improvement of the local search strategies.In this paper, introduce the basic topological characteristics, topological models and search strategies in the complex network, and then compare them. Analyze the defect causes of high degree seeking. Point out that there is a dividing value, makes the search process conform to imagine of search by degree sequence, to ensure the efficient of high degree seeking. Based on it, propose that divide the complex network into two parts according to node degree. Adopt the maximum degree search strategy for the nodes that degree less than it, and adopt the minimum clustering coefficient search strategy for the nodes that degree not less than it. And then design the complex network search strategy combined with Max degree and Min clustering coefficient. In this paper, complete task that analyze and dispose the existing data sets about real complex network, convert a data set contained adjacency matrix into a array, extract and calculate the relevant local information of node, and then achieve the search process of the maximum degree search strategy, the minimum clustering coefficient search strategy, the maximum-minimum degree search strategy and the complex network search strategy combined with Max degree and Min clustering coefficient.This article completes the relevant simulation test, used certain data sets with the various complex network topological characteristics. According to the average search steps and the average search time, compare, analyze and evaluate search effect of these complex network search strategy. Verify the correctness and validity of the complex network search strategy combined with Max degree and Min clustering coefficient.