Character relationship graph construction method and system based on deep learning

A person relationship and deep learning technology, applied in the field of deep learning-based person relationship graph construction, can solve problems such as inability to accurately represent multi-valued attributes, and achieve the effect of solving information filling problems, accurate information, and accurate character attributes.

Active Publication Date: 2020-08-14
HUAZHONG UNIV OF SCI & TECH
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  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

[0008] Aiming at the defects and improvement needs of the prior art, the present invention provides a method and system for constructing a char

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  • Character relationship graph construction method and system based on deep learning
  • Character relationship graph construction method and system based on deep learning
  • Character relationship graph construction method and system based on deep learning

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Embodiment Construction

[0060] 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. The characteristics, operations or characteristics described in the specification can be combined in any appropriate manner to form various embodiments. At the same time, the steps or actions in the method description can also be exchanged or adjusted in a manner obvious to those skilled in the art. Therefore, various sequences in the specification and drawings are only for clearly describing a certain embodiment, and do not mean a necessary sequence, unless otherwise stated that a certain sequence must be followed. In addition, the technical features involved in the various embodiments of the prese...

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Abstract

The invention discloses a figure relation graph construction method and system based on deep learning, and the method comprises the steps: crawling an electronic text to acquire an initial corpus which comprises figure information; labeling character attributes in the initial corpus to obtain sample data, and preprocessing the sample data; setting model hyper-parameters, and establishing a deep learning model in combination with the preprocessed sample data; defining a hierarchical character information template, extracting character attribute information based on the deep learning model, screening the character attribute information, and filling the character information template; and constructing a character relationship graph by utilizing the filled character information template and apredefined character relationship entity. Thus, the problem of finding and extracting the multi-value character attributes and the character relations existing in the scattered text can be solved, andthen the accuracy and the information richness of character relation graph construction are improved.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence, and more specifically, to a method and system for constructing a character relationship map based on deep learning. Background technique [0002] The character relationship graph is to extract various attributes of the characters from the text, and describe the concepts, entities and relationships related to the characters in the objective world in a structured form. With the development of the Internet, information is growing explosively. It is no longer realistic to rely on manual analysis, processing and understanding of massive text data. The character relationship graph provides a solution for people to efficiently analyze, process and understand the relationship between characters from massive texts. It plays an increasingly important role in many industries such as finance, law, and scientific research. It provides intelligent question answering and decision analysi...

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Application Information

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IPC IPC(8): G06F16/36G06F16/34G06F40/186G06N3/04G06N3/08
CPCG06F16/367G06F16/34G06F40/186G06N3/08G06N3/045Y02D10/00
Inventor 李瑞轩张纯鹏辜希武李玉华
Owner HUAZHONG UNIV OF SCI & TECH
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