IZ: An improved greedy algorithm for influence maximization under threshold model

Influence maximization is a problem for finding a set of seeds to maximize the spread of information in the network. In this article we bring out a context, which is called influence zone. It´s very helpful for us to efficient solve the influence maximization problem. The algorithm which is based on it the original greedy algorithm of efficiency and reduce its running time. We evaluate our algorithms by experiments on serval different synthetic networks. During the experiments we also evaluate the relation of algorithm´s efficiency and the influence zone factor.