A method and system for extracting a news event based on a neural network. The method comprises the steps of: carrying out data pre-processing on original text of a training corpus; introducing an event sentence sequence represented by a word vector into a bidirectional long- and short-term memory network, and using the bidirectional long- and short-term memory network to carry out training so as to obtain a semantic feature of each candidate trigger word; introducing the event sentence sequence represented by a word vector into a convolutional neural network, and using the convolutional neural network to carry out training so as to obtain a global feature of an event sentence in which the candidate trigger word is; and according to the semantic feature of the candidate trigger word and the global feature of the sentence in which the candidate trigger word is, using softmax as a classifier to classify each candidate trigger word, so as to find a trigger word of a news event, and according to the type of the trigger word, determining the type to which the event belongs. The method and system can quickly and accurately extract a news event and process a news event included in a non-standard sentence, and have the characteristics of high efficiency and universal applicability.
METHOD AND SYSTEM FOR EXTRACTING NEWS EVENT BASED ON NEURAL NETWORK