An end-to-end intent recognition system and method based on memory forgetting device

Abstract

The invention discloses an end-to-end intent recognition system and method based on a memory forgetting device, which includes a data preprocessing unit, which performs sentence-level vector representation on input sentences to obtain sentence vectors for each sentence; the input sentences include several above and The current question; the contextual intention recognition unit, which performs intention recognition and calculation on the sentence vector of the input sentence, and obtains the intention combined with the context prediction, the integrity of the current question sentence, and the attention weight of the input sentence; Sentence vectors perform intent recognition calculations to obtain the intent of a single sentence; the contextual intent determination unit determines whether the intent of the current question is the intent of a single sentence or the intent of context prediction according to the integrity of the current question sentence and the attention weight of the input sentence. It can effectively identify the importance of the above text to the current question sentence, take into account both the above text and the current question sentence, and ensure the lossless transmission of information.

Description

technical field [0001] The invention belongs to the technical field of computers, and in particular relates to an end-to-end intention recognition system and method based on a memory forgetting device. Background technique [0002] With the development and popularization of the Internet, online shopping is the living habit of most people. People usually need to communicate with merchant customer service to obtain pre-sale, in-sale and after-sale information during shopping. However, traditional real-person customer service cannot satisfy the growing consumer groups. , in customer service, how to provide customers with faster response and more accurate answers is a huge challenge for e-commerce customer service. Robot customer service is the first choice to solve this problem. A response system that provides answers to questions. The semantic recognition system is the core module. Its technical core is natural language processing technology. The earliest method is to identify...

AI Technical Summary

Problems solved by technology

In this scheme, LSTM is based on vocabulary-level memory and forgetting, which cannot cover sentences very well, and only pays attention to the relationship between the current question and the above sentence. When all the above questions have nothing to do with the current question, it will Cause recognition error

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