Intelligent auxiliary learning system based on knowledge graph and edge calculation

A knowledge map and edge computing technology, applied in the field of assisted learning, can solve the problems of insensitivity and other problems, and achieve the effect of avoiding insensitivity, reducing the occupation of network resources, and learning targeted and accurate

A knowledge map and edge computing technology, applied in the field of assisted learning, can solve the problems of insensitivity and other problems, and achieve the effect of avoiding insensitivity, reducing the occupation of network resources, and learning targeted and accurate

CN112015920APending Publication Date: 2020-12-01CHONGQING RADIO & TV UNIV
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  • Intelligent auxiliary learning system based on knowledge graph and edge calculation

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Embodiment Construction

[0018] In order to make the purpose, technical solution and advantages of the present invention clearer, the present invention will be further elaborated below in conjunction with the accompanying drawings.

[0019] In this example, see figure 1 As shown, the present invention proposes an intelligent assisted learning system based on knowledge graph and edge computing, including a natural language processing module, a dialogue management module, a knowledge graph module and a natural language generation module;

[0020] The natural language processing module converts the course question text and voice data input by the learner into the internal representation data of the machine; accesses the knowledge graph module in the server through edge computing, and with the assistance of the knowledge graph module, parses the input data and obtains the language identifying data;

[0021] The dialogue management module synthesizes the parsed language recognition data input by the learn...

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Abstract

The invention discloses an intelligent auxiliary learning system based on a knowledge graph and edge calculation. The invention includes converting course question characters and voice data input by alearner into internal representation data of a machine; accessing a knowledge graph module in the server through edge computing, and analyzing the input data under the assistance of the knowledge graph module to obtain language recognition data; synthesizing the analyzed language recognition data input by the learner and the corresponding learning information returned by the knowledge graph module to generate a related question answer; feeding back to learners. According to the invention, intelligent auxiliary learning can be realized; personalized learning services are provided for learners,the learners can obtain effective and accurate learning schemes, the recognition efficiency is improved, resource waste is reduced, accurate recognition can be achieved without establishing a huge recognition database, occupied network resources are reduced, and the phenomena of insensitive reaction, jamming and the like are avoided.

Description

technical field [0001] The invention belongs to the technical field of assisted learning, in particular to an intelligent assisted learning system based on knowledge graphs and edge computing. Background technique [0002] With the continuous development of science and technology, technological products have gradually integrated into our lives. Scientific and technological products are no longer far away, but have penetrated into every detail of our daily life. And learning is an indispensable part of our life, especially for primary and middle school students, daily life is learning. Learning aids can effectively help students learn independently and answer questions and solve problems for students in a timely manner. [0003] However, the existing learning aids have a single structure, cannot provide learners with personalized services, and the response effect is poor, often answering questions that are not asked, which disturbs the child's thinking and prevents the child...

Claims

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Application Information

Patent Timeline
01 Dec 2020
Publication
CN112015920A
IPC
G06F16/36; G06F16/332; G06F16/33; G06F40/30; G06Q50/20; G06N3/04
CPC
G06F16/367; G06F16/3329; G06F16/3344; G06F40/30; G06Q50/205; G06N3/045
Inventors
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