NEURAL NETWORK AND ATTENTION MECHANISM-BASED INFORMATION RELATION EXTRACTION METHOD

摘要

The present invention relates to the fields of recurrent neural networks, natural language processing and information analysis combined with attention mechanisms, and provided thereby are a neural network and an attention mechanism-based information relation extraction method, which are used for solving the problems of large workload and low generalization in existing information analysis systems that are mostly based on artificially constructed knowledge bases. The specific implementation of the method comprises a training phase and an application phase. In the training phase, first a user dictionary is constructed and word vectors are trained, a training set is constructed from within a historical information database, a corpus is pre-processed, and then neural network model training is conducted; and in the application phase, information is obtained, the information is pre-processed, an information relation extraction task may be automatically completed while supporting user dictionary expansion and error correction determination, the result of which is added to a training neural network model having an incremental training set. The information relation extraction method can find relationship between pieces of information, provide a basis for event context integration and decision making, and has a wide range of application value.