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Statement similarity determination method and device, electronic device and readable storage medium

A technology for determining method and similarity, applied in the field of intelligent answering, can solve problems such as low accuracy of sentence similarity and affecting user experience

Active Publication Date: 2019-07-05
北京九狐时代智能科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in natural language, words that are far apart also have interdependence in semantics. Therefore, the accuracy of sentence similarity determination in the existing sentence similarity determination method is not high, resulting in intelligent sentence answering process. There is a situation where the answer is not what the question is asked, which affects the user's experience

Method used

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  • Statement similarity determination method and device, electronic device and readable storage medium
  • Statement similarity determination method and device, electronic device and readable storage medium
  • Statement similarity determination method and device, electronic device and readable storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0078] Such as figure 1 As shown, it is a method for determining sentence similarity provided in Embodiment 1 of the present application, including:

[0079] S101: Based on the first vocabulary feature vectors of each first vocabulary in the input sentence, determine the first semantic feature vector corresponding to each first vocabulary; and, based on the second vocabulary feature vector of each second vocabulary in the standard sentence, determine the corresponding Second semantic feature vectors corresponding to each second vocabulary.

[0080] In the specific implementation process, the client obtains the input sentences and preprocesses the input sentences. When constructing a question corpus storing standard sentences, it also needs to preprocess the historical input sentences. Taking the construction of a question corpus storing standard sentences as an example, after obtaining historical input sentences, external data needs to be loaded first.

[0081] When building...

Embodiment 2

[0122] Such as figure 2 As shown, Embodiment 2 of the present application also provides a sentence similarity determining device 200, including:

[0123] Feature extraction module 201, for determining the first semantic feature vector corresponding to each first vocabulary based on the first vocabulary feature vector of each first vocabulary in the input sentence; and, based on the second vocabulary of each second vocabulary in the standard sentence A feature vector, determining a second semantic feature vector corresponding to each second vocabulary;

[0124] The weight calculation module 202 is configured to determine the first weight corresponding to each first semantic feature vector based on the first semantic feature vector corresponding to each first vocabulary; and determine the first weight corresponding to each second semantic feature vector based on the second semantic feature vector corresponding to each second vocabulary. The second weight corresponding to the t...

Embodiment 3

[0154] refer to image 3 As shown, the electronic device 300 provided in Embodiment 3 of the present application includes a processor 301 , a memory 302 , and a bus 303 .

[0155] The memory 302 stores machine-readable instructions executable by the processor 301 (for example, figure 2 The feature extraction module 201, the weight calculation module 202 and the execution instructions corresponding to the similarity calculation module 203, etc.), when the electronic device 300 is running, the processor 301 communicates with the memory 302 through the bus 303, and the When the machine-readable instructions are executed by the processor 301, the following processes are performed:

[0156] Based on the first vocabulary feature vectors of each first vocabulary in the input sentence, determine the first semantic feature vector corresponding to each first vocabulary; The second semantic feature vectors corresponding to the two words respectively;

[0157] Based on the first seman...

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Abstract

The invention provides a statement similarity determination method and device, an electronic device and a readable storage medium. The method comprises the following steps of: determining first semantic feature vectors corresponding to the first vocabularies in the input statement and first weights of the first semantic feature vectors, and determining a second semantic feature vector corresponding to each second vocabulary in the standard statement and a second weight of each second semantic feature vector, and calculating the similarity between the input statement and the standard statementbased on the first semantic feature vector, the first weight, the second semantic feature vector and the second weight. According to the method and the device, the semantic dependency relationship ofthe vocabularies far away from each other is represented through the first weight and the second weight, so that the similarity between the input statement and the standard statement is determined, the statement similarity determination accuracy is improved, the condition that the intelligent statement responds not to questions in the response process is reduced, and the intelligent statement response accuracy is improved.

Description

technical field [0001] The present application relates to the technical field of intelligent responses, in particular to a method, device, electronic equipment and readable storage medium for determining sentence similarity. Background technique [0002] In fields such as finance and shopping, intelligent sentence answering has important and extensive application value. The traditional method is to search and answer knowledge manually. The cost of manual answering is high and the quality is difficult to control. Therefore, intelligent sentence answering is imperative. [0003] The sentence similarity determination is the most important part of the intelligent sentence response. The existing sentence similarity determination method only analyzes each input sentence and each vocabulary in the standard sentence in sequence according to the word order of the input sentence and the standard sentence. , to extract semantic features. However, in natural language, words that are f...

Claims

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Application Information

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IPC IPC(8): G06F16/332G06F16/33G06F17/27G06K9/62
CPCG06F40/242G06F40/211G06F40/289G06F18/22
Inventor 韩亮
Owner 北京九狐时代智能科技有限公司
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