Shortest Path Approximate Algorithm for Complex Network Analysis

The tremendous scale of the social networks mined from Internet is the main obstacle of a social network analysis application. The bottleneck of many network analysis algorithms is the extortionate computational complexity of calculating the shortest path. Real-World networks usually exhibit the same topological features as complex networks such as the "scale-free" and etc,which indicate the intrinsic laws of the shortest paths in complex networks. Based on the topological features of real-world networks,a novel shortest path approximate algorithm which uses an existent short path passing through some local center nodes to estimate the shortest path in complex networks,is proposed. This paper illustrates the advantage and feasibility of incorporating the proposed algorithm within the network properties,which suggests a new idea for complex social network analysis. The proposed algorithm has been evaluated both on synthetic network stage and real world network stage. Experimental results show that the proposed algorithm can largely reduce the computational complexity and remain highly effective in complex networks.

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