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1. (WO2018218707) NEURAL NETWORK AND ATTENTION MECHANISM-BASED INFORMATION RELATION EXTRACTION METHOD

Pub. No.:    WO/2018/218707    International Application No.:    PCT/CN2017/089137
Publication Date: Fri Dec 07 00:59:59 CET 2018 International Filing Date: Wed Jun 21 01:59:59 CEST 2017
IPC: G06F 17/27
Applicants: CHINA UNIVERSITY OF MINING AND TECHNOLOGY
中国矿业大学
Inventors: LIU, Bing
刘兵
ZHOU, Yong
周勇
ZHANG, Runyan
张润岩
WANG, Chongqiu
王重秋
Title: NEURAL NETWORK AND ATTENTION MECHANISM-BASED INFORMATION RELATION EXTRACTION METHOD
Abstract:
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.