Abstract
With the gradual improvement of my country's informatization construction, people need more intelligent and accurate information retrieval and automatic question answering and other services in the field of artificial intelligence. In order to continuously improve the performance of the algorithm to provide more efficient and comfortable services, a large number of researchers have invested in the research of natural language processing.Text matching is the core and basic problem in the field of natural language processing. It has experienced from the early traditional text matching methods based on statistics to the deep text matching methods in recent years. This paper studies several popular deep learning text matching methods, including single-semantic text matching, multi-semantic text matching and attention mechanism text matching. On the basis of the currently widely used algorithms, a multi-channel matching pyramid model, a text matching model of cyclic attention mechanism and a model stacking integration algorithm of dynamic parameters are proposed, and the integration is realized by using natural language processing technology.
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