Dialogue data interaction processing method and device based on recurrent neural network

Abstract

The invention provides a dialogue data interaction processing method based on a recurrent neural network. The method comprises the following steps: receiving a dialogue input statement of a user; carrying out knowledge base matching calculation, and judging whether a knowledge base has a problem statement, the matching degree between which and the dialogue input statement reaches a preset value; if not, requesting a dialogue generation model to give an answer to the dialogue input statement, wherein a coding layer of the dialogue generation model is constructed into the recurrent neural network, analyzing the dialogue input statement in the recurrent neural network to obtain a middle vector expressing problem meanings, and a decoding layer of the dialogue generation model is also constructed into the recurrent neural network, analyzing the middle vector in the recurrent neural network to obtain an answer vector group expressing answer meanings; and taking the answer vector group as an answer output statement and outputting the answer output statement. The method can enable human-machine interaction to be smoother; and answers given by the dialogue generation model can further enable the knowledge base to be expanded and updated.

Description

technical field [0001] The invention relates to the field of intelligent robots, in particular to a method and device for interactively processing dialogue data based on a cyclic neural network. Background technique [0002] Chatterbot (chatterbot) is a program used to simulate human dialogue or chat. The reason for chatbots is that the developers put the answers they are interested in into the database. When a question is thrown to the chatbot, it uses the similarity matching algorithm to find the most similar question from the database, and then based on the question and The corresponding relationship of the answer, give the most appropriate answer, and reply to its chat partner. [0003] However, in the current robot chat scenario, when the same or similar question matching the user's requested question cannot be found in the robot knowledge base, the robot cannot return the correct or appropriate answer to the user. [0004] In addition to the problem of limited knowle...

AI Technical Summary

Problems solved by technology

[0003] However, in the current robot chat scenario, when the same or similar questions that match the user's requested question cannot be found in the robot knowledge base, the robot cannot return the correct or appropriate answer to the user.

[0004] In addition to the limited knowledge base of the robot, the limitation of the existing technology will also lead to errors in semantic understanding, thus mak

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