Abstract:

In order to find a reasonable network structure in big data, we present a local search algorithm suitable for big data. Aiming at the uncertainty of the initial nodes and the timeconsuming fitness function computation, we introduce key local nodes and improve the fitness function to reduce the time consumption. Experimental results show that compared with classical algorithms the time consumption of the improved algorithm does not change much in smallscale data networks but is less in largescale data networks, which demonstrates that the proposed algorithm is feasible and effective and can be applied to the clustering of large-scale data.

Key words: big data;clustering;local;fitness function