Intelligent question and answer sentence pair semantic matching method and device for government affair consultation service

Abstract

The invention discloses an intelligent question and answer sentence pair semantic matching method and device for government affair consultation service, and belongs to the technical field of artificial intelligence and natural language processing. The technical problem to be solved by the invention is how to capture deeper semantic context features and interaction information between sentences andreduce the loss of semantic information, so intelligent semantic matching of sentence pairs is realized. The adopted technical scheme is as follows: a sentence pair semantic matching model composed of a multi-granularity embedding module, a gating deep feature residual fusion network module, a semantic feature interaction matching module and a label prediction module is constructed and trained; and gated deep feature residual fusion expression of sentence information is achieved, meanwhile, final matching tensors of sentence pairs are generated through an attention mechanism and a gating mechanism, and the matching degree of the sentence pairs is judged, so that the purpose of intelligent semantic matching of the sentence pairs is achieved. The device comprises a sentence pair semantic matching knowledge base construction unit, a training data set generation unit, a sentence pair semantic matching model construction unit and a sentence pair semantic matching model training unit.

Description

technical field [0001] The invention relates to the technical fields of artificial intelligence and natural language processing, in particular to an intelligent question-and-answer sentence-pair semantic matching method for government consultation services. Background technique [0002] The people need to understand the relevant policies and documents formulated by the government when handling their daily affairs. In order to better serve the people, governments at all levels need to set up government consultation related service agencies to provide government consultation for the people. As the demand for government consultation continues to grow, the work pressure of relevant institutions continues to increase. Although the demand for government affairs consultation is constantly increasing, the vast majority of consultations are repeated consultations. For these repeated consultations, the historical consultation library can be mined and answered automatically. Intelli...

AI Technical Summary

Problems solved by technology

However, the representation ability of a single-layer network is limited after all. Therefore, in order to improve the representation ability of the network and extract deeper and richer semantic features, the depth of the network is usually increased.

However, the encoding results of each layer in the deep network structure are not all valid information. In this case, two problems will arise: first, if only the output of the last layer of the network is taken as the encoding result, then it must be It will cause the loss of semantic information; second, if the output results of each layer of the network are directly combined, such as connection or addition, then the final encoding result will inevitably have a lot of noise

Therefore, the existing deep network structure still has the above-mentioned drawbacks that cannot be ignored for text semantic coding.

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