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A method and system for semantic analysis of human-computer dialogue

A technology of semantic analysis and human-computer dialogue, applied in special data processing applications, instruments, electronic digital data processing, etc., can solve problems such as inability to analyze user semantics, inaccurate identification of user intentions, etc., and achieve the effect of good input

Active Publication Date: 2018-03-30
BEIJING JINGDONG SHANGKE INFORMATION TECH CO LTD +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] Based on this, it is necessary to provide a semantic analysis method and system for man-machine dialogue in order to solve the technical problem that the semantic analysis of the user cannot be performed in the prior art, so that the user's intention is not accurately recognized.

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  • A method and system for semantic analysis of human-computer dialogue
  • A method and system for semantic analysis of human-computer dialogue
  • A method and system for semantic analysis of human-computer dialogue

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Embodiment Construction

[0019] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.

[0020] Such as figure 1 Shown is a work flow chart of a semantic analysis method of a man-machine dialogue of the present invention, including:

[0021] Step S101, comprising: obtaining training corpus including a plurality of training sentences, training an emotion function through the training corpus, and calculating a corresponding emotion value for the input sentence by the emotion function;

[0022] Step S102, comprising: acquiring a user input sentence, and inputting the user input sentence into the emotion function to obtain an emotion value related to the user input sentence as a user emotion value;

[0023] Step S103 includes: selecting an answer that satisfies the user's emotional value from a plurality of answers related to the user input sentence as a semantic analysis answer, and displaying the semantic analysis answer. ...

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Abstract

The invention discloses a semantic analysis method and system for man-machine dialogue. The method includes: obtaining training corpus, training an emotional function through the training corpus, and calculating the corresponding emotional value of the input sentence by the emotional function; obtaining user input sentence , after the user input sentence is input into the emotion function, the emotional value of the user input sentence is obtained as the user emotion value; from a plurality of answers related to the user input sentence, select the answer that satisfies the user emotion The response answer of the value is used as a semantic analysis answer, and the semantic analysis answer is displayed. The present invention obtains the emotional function for calculating the emotional value through function training, so that the corresponding emotional value can be calculated from the user input sentence, and the answer that satisfies the user's emotional value can be selected from a plurality of answers related to the user input sentence Answers serve as semantically analyzed answers to better answer user input.

Description

technical field [0001] The invention relates to the technical field related to man-machine dialogue, in particular to a semantic analysis method and system for man-machine dialogue. Background technique [0002] In the current man-machine dialogue question answering system, when the user enters a question, identifying the user's intention to ask is the core part of the entire question answering system. The intention recognition is correct but the accuracy rate is too low, which will cause the answer to be returned to the user later. There are so many questions that it is impossible to choose the best answer; the wrong intention recognition will cause the inability to understand the meaning of the user, thus providing the user with an unwanted answer or being unable to give the answer directly. Existing technical practices are: [0003] Model prediction: This method is mainly to manually classify and label the corpus, and then train a model through a decision tree or classif...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/27
Inventor 陶玮
Owner BEIJING JINGDONG SHANGKE INFORMATION TECH CO LTD