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Homework duplicate checking method based on deep learning

A deep learning and homework technology, applied in text database query, biological neural network model, semantic analysis, etc., can solve problems such as poor anti-interference effect, achieve the effect of long time to solve and improve the efficiency of duplicate checking

Pending Publication Date: 2021-06-22
SOUTH CHINA UNIV OF TECH +1
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to overcome the shortcomings and deficiencies of the prior art, and propose a homework plagiarism check method based on deep learning, which can accurately find out the text content with similar semantics in the homework, and solve the problem of poor anti-interference effect of many plagiarism detection methods

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  • Homework duplicate checking method based on deep learning

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Embodiment Construction

[0038] The present invention will be further described in detail below in conjunction with the embodiments and the accompanying drawings, but the embodiments of the present invention are not limited thereto.

[0039] Such as figure 1 As shown, the deep learning-based job duplication check method provided in this embodiment includes the following steps:

[0040] 1) Obtain student coursework data and homework template files, and read the content of the files; among them, student coursework data refers to student homework obtained from courses on the online learning platform; homework template files refer to the online learning platform. A file in the format of assignments submitted by your instructor or teaching assistant in the course.

[0041] 2) Judging the format of the homework template, processing the obtained homework according to the topic, and judging whether the questions in the homework are subjective questions or objective questions. The details are as follows:

[...

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Abstract

The invention discloses a homework duplicate checking method based on deep learning, and the method comprises the steps: obtaining student curriculum homework data and a homework template file, judging the format of a homework template, carrying out the question-cutting processing of the obtained homework, judging whether the question in the homework is a subjective question or an objective question, carrying out the text preprocessing of the answer of the subjective question in the homework after the question-cutting, employing the deep learning technology (namely a convolutional neural network model) to calculate the similarity between student homework, analyzing a similarity calculation result, clustering the student homework with high similarity, and generating a similarity report. In order to facilitate a teacher to check similar content conditions, similar contents among similar homework are marked. According to the method, text contents with similar job semantics can be found out, and the problem that many plagiarism detection methods are poor in anti-interference effect is solved.

Description

technical field [0001] The invention relates to the technical field of plagiarism checking of students' homework, in particular to a method for plagiarism checking of homework based on deep learning. Background technique [0002] In online assisted teaching in colleges and universities, electronic documents have become one of the main forms of student assignment submission. With people's emphasis on academic ethics, how to assist teachers to find plagiarized content in homework submitted by students has become a research hotspot. [0003] At present, there are many plagiarism detection systems, such as the domestic China National Knowledge Infrastructure (CNKI) academic misconduct literature detection system, and foreign systems such as Turnitin, PlagScan, and Dupli Checker. These systems can help teachers find plagiarized parts of students' submitted work, but because these systems use the Internet as a source of plagiarism, it is difficult to find plagiarized relationship...

Claims

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Application Information

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IPC IPC(8): G06F40/194G06F16/33G06F16/338G06F40/263G06F40/268G06F40/216G06F40/284G06F40/30G06F16/35G06N3/04G06Q50/20
CPCG06F40/194G06F16/3344G06F16/3334G06F16/3335G06F16/338G06F40/263G06F40/268G06F40/216G06F40/284G06F40/30G06F16/353G06Q50/205G06N3/045
Inventor 张凌胡布焕张晶
Owner SOUTH CHINA UNIV OF TECH
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