Multi-attribute spectral clustering emergency detection based on word correlation feature - Weijin JIANG; Yang WANG; Xiaoliang LIU; Sijian LYU (Tongxin xuebao, 2020)
For current methods for extracting emergencies had problems of low accuracy and low efficiency, an emergency detection method based on the characteristics of word correlation was proposed, which could quickly detect emergency events from the social network data stream, so that relevant decision makers could take timely and effective measures to deal with, making the negative impact of emergencies can be reduced as much as possible to maintain social stability.The simulation results show that the emergency event detection method has a better event detection effect in the real-time blog post data stream.Compared with the existing methods, the proposed method can meet the needs of emergency detection.Not only the detailed information of the sub-events can be detected, but also the related information of the events can be accurately detected.