Method for obtaining question and answer pairs from unstructured text based on deep learning

An unstructured, deep learning technology, applied in neural architecture, special data processing applications, instruments, etc., can solve problems such as difficulty in acquiring question-answer pairs and speeding up the construction of knowledge bases

Active Publication Date: 2019-08-09
北京中科汇联科技股份有限公司
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Problems solved by technology

[0016] Aiming at the defects existing in the prior art, the purpose of the present invention is to provide a method based on deep learning to obtain question-answer pairs from unstructured texts, aiming at the problem that it is difficult to obtain question-answer pairs, by making effective use of easy-to-acquire unstructured text Document resources, combined with the use of deep neural network models, automatically and efficiently obtain large-scale question-answer pairs for manual proofreading and supplementary use, reducing the cost of building knowledge bases and speeding up the construction of knowledge bases

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  • Method for obtaining question and answer pairs from unstructured text based on deep learning
  • Method for obtaining question and answer pairs from unstructured text based on deep learning
  • Method for obtaining question and answer pairs from unstructured text based on deep learning

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[0104] The present invention will be described in further detail below in conjunction with the accompanying drawings. When the following description refers to the accompanying drawings, the same numerals in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatuses and methods consistent with aspects of the present disclosure as recited in the appended claims.

[0105] like figure 1 , 2 As shown, the method for obtaining question-answer pairs from unstructured text based on deep learning described in the present invention comprises the following steps:

[0106] Text normalization;

[0107] Sentence classification and pairing and key phrase extraction based on the deep neural network model;

[0108] Question-answer pair acquisition inside the text;

[0109] Q...

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Abstract

The invention relates to a method for obtaining question and answer pairs from an unstructured text based on deep learning. The method comprises the following steps of performing text normalization processing; based on a deep neural network model, sentence classification and pairing and key phrase extraction are carried out; obtaining question and answer pairs in the text; crawling question and answer pairs outside the text; question and answer pair summary duplicate removal. According to the method, for the problem that question and answer pairs are difficult to obtain, the scale question andanswer pairs are automatically and efficiently obtained by effectively utilizing easily-obtained unstructured document resources in combination with the use of the deep neural network model for manual proofreading and supplementary use, so that the knowledge base construction cost is reduced, and the knowledge base construction speed is increased.

Description

technical field [0001] The present invention relates to the technical field of natural language question answering system knowledge extraction, in particular to the field of question answer pair extraction, specifically a method for obtaining question answer pairs from unstructured text based on deep learning. Background technique [0002] Natural language processing (NLP, natural language processing) is a field of computer science, artificial intelligence, and linguistics that focuses on the interaction between computers and human (natural) language. It is an important direction in the field of computer science and artificial intelligence. [0003] Natural language processing is a science that integrates linguistics, computer science, and mathematics. The research in this field will involve natural language, that is, the language that people use every day, so it is closely related to the study of linguistics. There are important differences. Natural language processing is ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/332G06F17/27G06N3/04
CPCG06F16/3329G06F40/211G06N3/045
Inventor 王丙栋朱江平游世学
Owner 北京中科汇联科技股份有限公司
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