Abstract
Text semantic matching is an important issue in natural language processing, and it is widely used in question answering systems, dialogue systems, and information retrieval. Text matching models can be divided into representation-based text matching models and interaction-based text matching models. Aiming at the problem that the existing text matching models tend to ignore the global information, a Chinese text semantic matching model oriented to information interaction is proposed. This model uses interactive attention and self-attention to make the text's own structure for information interaction, and at the same time increases the deep semantic interaction of the two texts, and obtains abundant semantic information vectors. Experiments show that the information interaction-oriented semantic matching model proposed in this paper is superior to the traditional model on the verified Chinese text data set.
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