Text semantic matching method and apparatus

Abstract

The invention provides a text semantic matching method. The method comprises the steps of obtaining total vectors by using word vectors and character vectors corresponding to words and characters in ato-be-processed text; performing convolution processing, averaging processing and bidirectional LSTM processing on the total vectors, wherein an LSTM method without an attention mechanism is adoptedduring basic text processing, and an LSTM method with the attention mechanism is adopted during target text processing; obtaining pooling vectors; and taking the similarity of the two pooling vectorsas the similarity of two texts. According to the method, not only a semantic relationship among the words in the text but also a semantic relationship among the characters are considered; not only a positive semantic relationship between the characters and the words but also a negative semantic relationship between the characters and the words are considered; and multiple text matching models arecomprehensively applied, so that feature information among text contexts is expressed more comprehensively, accurately and fully, and the text matching accuracy is improved.

Description

technical field [0001] The present application belongs to the field of natural language processing, and in particular relates to a method and device for text semantic matching. Background technique [0002] Text matching is used to obtain the degree of correlation or similarity between two texts. It is a core technology in the field of natural language processing. It can effectively represent and extract the semantic information of texts. It has important significance in the fields of information retrieval, information extraction, and automatic question answering. . [0003] The existing text matching technology mainly converts the two texts into the form of vectors, and then calculates the similarity of the two vectors by cosine, Euclidean distance and other methods, and uses the obtained similarity to represent the text matching of the two texts. result. [0004] With the rise of deep learning neural networks, CNN (Convolutional Neural Networks, convolutional neural netw...

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Problems solved by technology

[0008] This application provides a text semantic matching method and device, which organically combines multiple text representations and text semantic matching methods to solve the problems of lack of sequence information, gradient disappearance or gradient explosion in traditional text semantic matching methods

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