Man-machine interactive semantic analysis method and system

A technology of semantic analysis and man-machine dialogue, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as inability to analyze user semantics and inaccurate recognition of user intentions, and achieve good input effects

Active Publication Date: 2015-07-29
BEIJING JINGDONG SHANGKE INFORMATION TECH CO LTD +1
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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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  • Man-machine interactive semantic analysis method and system
  • Man-machine interactive semantic analysis method and system

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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] like 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 man-machine interactive semantic analysis method and system. The method comprises the following steps of obtaining a training corpus, establishing an emotion function through the training corpus by training, and calculating a corresponding emotion value for an input sentence according to the emotion function; obtaining the sentence input by a user, inputting the sentence input by the user into the emotion function, and obtaining the emotion value relating to the sentence input by the user as a user emotion value; selecting a responding answer satisfying the user emotion value from multiple responding answers related with the sentence input by the user as a semantic analysis answer, and displaying the semantic analysis answer. According to the method and the system provided by the invention, the emotion function for calculating the emotion value is obtained through function training, so that the emotion value corresponding to the sentence input by the user can be calculated and the responding answer satisfying the user emotion value can be selected from the multiple responding answers related with the sentence input by the user as the semantic analysis answer. Therefore, the input of the user can be better answered.

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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IPC IPC(8): G06F17/27
Inventor 陶玮
Owner BEIJING JINGDONG SHANGKE INFORMATION TECH CO LTD
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