Text abstract automatic generation method and system fused with pre-training model

An automatic generation and pre-training technology, applied in neural learning methods, biological neural network models, unstructured text data retrieval, etc., can solve problems such as difficult to process long text summaries

Pending Publication Date: 2021-05-07
CHONGQING UNIV OF POSTS & TELECOMM
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the existence of long-distance dependence problems, generative models based on RNN or CNN are often difficult to handle long text summaries

Method used

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  • Text abstract automatic generation method and system fused with pre-training model
  • Text abstract automatic generation method and system fused with pre-training model
  • Text abstract automatic generation method and system fused with pre-training model

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Embodiment Construction

[0063] Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the diagrams provided in the following embodiments are only schematically illustrating the basic concept of the present invention, and the following embodiments and the features in the embodiments can be combined with each other in the case of no conflict.

[0064] Wherein, the accompanying drawings are for illustrative purposes only, and represent only schematic diagrams, rather than physical drawings, and sh...

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Abstract

The invention relates to a text abstract automatic generation method and system fused with a pre-training model, and belongs to the technical field of text abstract automatic generation. According to the system, on the basis of a traditional Sequence-to-Sequence model and a Transformer framework, a BERT is used as an encoder to obtain context semantic features of an original text, meanwhile, a convolutional neural network is added to serve as gating, and keyword and key phrase screening is conducted on feature vectors. On the basis of using Transformer Decoder in a decoder stage, a pointer mechanism is added, so that the abstract generation model can better solve the problem of insufficient vocabulary (OOV) in the generation process, the readability of the generated abstract is improved, and the best abstract legal text is generated by adopting a beam search method in a final generation stage.

Description

[0001] The invention belongs to the technical field of automatic generation of text summaries, and relates to a method and system for automatically generating text summaries fused with a pre-training model. Background technique [0002] Automatic text summarization is becoming more and more important as the amount of text content on the Internet, news, papers, legal documents and other various documents grows exponentially. Manual summarization takes a lot of time, energy and cost, and becomes impractical when the text content is huge. Therefore, it is very necessary to perform a "dimension reduction" process on various texts. [0003] Text summarization is an important task of natural language processing and natural language generation. Its purpose is to use extraction or generation to obtain a short version of a given document while retaining the salient information of the given document. Current automatic summarization methods are either extractive, generative, or hybrid. ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/34G06F16/335G06F40/126G06F40/284G06N3/04G06N3/08
CPCG06F16/345G06F16/335G06F40/284G06F40/126G06N3/04G06N3/08
Inventor 邓维斌李云波胡峰王崇宇朱坤彭露
Owner CHONGQING UNIV OF POSTS & TELECOMM
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