Probabilistic Feature Association Algorithm of Soft Information

The situation assessment based on news events should consider the long-term trend of the events.In this paper,the long-term dictionary is introduced to characterize the long-term trend,and then,a probabilistic feature association algorithm is proposed for long-term features and current features.In order to obtain the full feature of the news event,the proposed algorithm firstly extracts long-term dictionary based on long-term text information collection of a news event.Besides,the probabilistic feature association algorithm,which is based on the similar degree of the keywords,is utilized to fuse the long-term feature into the current feature.In order to evaluate the association algorithm performance,both long-term association degree and class association degree are proposed.The experimental results show that the probabilistic feature association algorithm can introduce the long-term trend and improve the accuracy of situation assessment.