Text processing method based on sentence vector pre-training model and related equipment

A text processing and sentence vector technology, applied in the field of text processing based on the sentence vector pre-training model, can solve the problems of sentence vector, inability to obtain, not considering text grammatical relations, etc., to improve the accuracy, execution efficiency and accuracy. rate, the effect of enriching the input information

Active Publication Date: 2021-09-24
PING AN TECH (SHENZHEN) CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] However, the existing technology optimizes the model at the stage of obtaining sentence vectors, does not consider the grammatical relationship in the text, and cannot obtain better sentence vectors, which leads to low accuracy of text processing

Method used

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  • Text processing method based on sentence vector pre-training model and related equipment
  • Text processing method based on sentence vector pre-training model and related equipment
  • Text processing method based on sentence vector pre-training model and related equipment

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Experimental program
Comparison scheme
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Embodiment 1

[0050] figure 1 It is a flow chart of the text processing method based on the sentence vector pre-training model provided by Embodiment 1 of the present invention.

[0051] In this embodiment, the text processing method based on the sentence vector pre-training model can be applied to electronic devices, and for electronic devices that need to perform text processing based on the sentence vector pre-training model, the present invention can be directly integrated on the electronic device The text processing function based on the sentence vector pre-training model provided by the method, or run in the electronic device in the form of a software development kit (Software Development Kit, SDK).

[0052] Such as figure 1 As shown, the text processing method based on the sentence vector pre-training model specifically includes the following steps. According to different requirements, the order of the steps in the flow chart can be changed, and some of them can be omitted.

[0053...

Embodiment 2

[0107] Figure 4 It is a structural diagram of a text processing device based on a sentence vector pre-training model provided in Embodiment 2 of the present invention.

[0108] In some embodiments, the text processing device 40 based on the sentence vector pre-trained model may include a plurality of functional modules composed of program code segments. The program codes of each program segment in the text processing device 40 based on the sentence vector pre-training model can be stored in the memory of the electronic device, and executed by the at least one processor to execute (see for details Figure 1 to Figure 3 Description) The function of text processing based on the sentence vector pre-training model.

[0109] In this embodiment, the text processing device 40 based on the pre-trained sentence vector model can be divided into multiple functional modules according to the functions it performs. The functional modules may include: a receiving module 401 , a word segmen...

Embodiment 3

[0164] refer to Figure 5 As shown in , it is a schematic structural diagram of the electronic device provided by Embodiment 3 of the present invention. In a preferred embodiment of the present invention, the electronic device 5 includes a memory 51 , at least one processor 52 , at least one communication bus 53 and a transceiver 54 .

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Abstract

The invention relates to the technical field of artificial intelligence, and provides a text processing method based on a sentence vector pre-training model and related equipment, and the method comprises the steps: obtaining a target corpus text and a text processing task; performing word segmentation processing on the target corpus text to obtain a plurality of segmented words; constructing a sentence vector pre-training model comprising a grammatical relationship recognition layer and a grammatical relationship addition layer according to the task type of the text processing task; training a constructed sentence vector pre-training model corresponding to the task type of the text processing task according to the training set; and inputting the plurality of segmented words into the trained sentence vector pre-training model to obtain an execution result of the text processing task. According to the method, the grammatical relation recognition layer and the grammatical relation adding layer are added to the sentence vector pre-training model, the grammatical relation is fused into the target corpus text, input information during sentence vector extraction is enriched, better sentence vectors are obtained, and then the execution efficiency and accuracy of the text processing task are improved.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence, in particular to a text processing method and related equipment based on a sentence vector pre-training model. Background technique [0002] In the field of text processing, for text classification, semantic matching, etc., it is necessary to obtain sentence vectors and then perform classification, matching, and other calculations. The existing technology uses the RNN network to learn sentence vectors, or the BERT model to calculate the entire sentence to obtain sentence vectors. [0003] However, the existing technology optimizes the model in the stage of obtaining sentence vectors, without considering the grammatical relationship in the text, and cannot obtain better sentence vectors, which leads to low accuracy of text processing. [0004] Therefore, it is necessary to provide a fast and accurate text processing method. Contents of the invention [0005] In view of the above...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/04G06N3/08G06F40/289G06F40/295G06F40/253
CPCG06N3/08G06F40/289G06F40/295G06F40/253G06N3/044Y02D10/00
Inventor 孙超王健宗
Owner PING AN TECH (SHENZHEN) CO LTD
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