Network threat intelligence text key information extraction method based on weak supervised learning

The invention discloses a network threat intelligence text key information extraction method based on weak supervised learning, and the method comprises the steps: converting information extraction into a feature data space mapping task, combining a knowledge representation learning method, adopting an attention mechanism based on a local sequence, and utilizing a text theme label to extract key information of a network threat intelligence text; key information extraction of a weak supervised learning text is realized, the quality of the extracted information is verified by using a manual evaluation and confidence evaluation mode, and the information is ensured to be real, reliable and credible. The method comprises the following steps: training a more accurate, comparative and basis key information extraction model for a text, and hoping that the key information formed by the extraction model can reflect the actual semantic value of a sequence tag rationally; through a weak supervised learning strategy and t