A new method is proposed for modeling the news event evolution to precisely present the relationships between events. This method utilized the events timestamp, events content similarity, and events dependence between features to build a new event evolution model, and defined five different event evolution patterns to identify the seminal events, the intermediary and ending events. Ultimately, an event evolution graph model was constructed to present the underlying events relationship. Experiments were conducted, confirming that the proposed method is efficient for detecting event evolution, and improves performance of system.