Answer extraction method and system based on deep learning

A technology of answer extraction and deep learning, applied in instruments, network data indexing, computing, etc., can solve the problems of inability to recognize answers of similar words, low recognition accuracy, etc., to improve the function of evidence screening and filtering, and expand the breadth Effect

Inactive Publication Date: 2018-02-23
HUAZHONG UNIV OF SCI & TECH
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Problems solved by technology

[0004] Aiming at the above defects or improvement needs of the prior art, the present invention provides an answer extraction method and system based on deep learning, thereby solving t...

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  • Answer extraction method and system based on deep learning
  • Answer extraction method and system based on deep learning
  • Answer extraction method and system based on deep learning

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Embodiment Construction

[0035] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not constitute a conflict with each other.

[0036] Aiming at the questions raised by users, the invention uses the keywords to search the fragments of the answers related to the questions from the text database or based on the network after classifying the questions and extracting the keywords. Using knowledge extraction technology, according to a given ontology, it identifies and extracts factual knowledge that matches ontology from info...

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Abstract

The invention discloses an answer extraction method and system based on deep learning. wherein an implementation of the method includes the steps of collecting knowledge fragments related to the answer of a question to be answered according to keywords in the question to be answered; based on the type of the question to be answered, analyzing the part-of-speech tagging of the knowledge fragment, and using the knowledge fragment containing the type of the question to be answered as a candidate answer; using the trained word2vec model to calculate the similarity between the keywords and words contained in the knowledge fragment in the candidate answer, and finding words that meet the similarity requirements as target candidate answers; substituting the words in the target candidate answers into the question to be answered to obtain a number of target statements, sorting each target statement by judging semantic information of each target statement, and using the target statement with thehighest score as the target answer. Through the extraction method and system, the answers of multiple words with higher similarity can be found, thereby improving the accuracy of the system.

Description

technical field [0001] The invention belongs to the technical field of artificial intelligence and deep learning, and more specifically relates to an answer extraction method and system based on deep learning. Background technique [0002] Q&A robot refers to the natural language understanding technology as the core, which enables the computer to understand the questions raised by the user, realizes effective communication between humans and the computer, and provides powerful search capabilities to accurately answer the user's questions. Among them, the intelligent question answering system commonly used in computer customer service systems is an automatic question answering system, which is an artificial intelligence system that can understand users' questions and provide accurate answers through natural language technology. However, the current intelligent question answering system. [0003] Most of the existing question answering systems first perform word segmentation ...

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Application Information

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IPC IPC(8): G06F17/30G06F17/27
CPCG06F16/3329G06F16/3344G06F16/951G06F40/211G06F40/284
Inventor 路松峰万飞黄炎徐科王同洋
Owner HUAZHONG UNIV OF SCI & TECH
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