文本中流程图图像的抄袭检测

Behnam Hadi, M. Kargar
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引用次数: 3

摘要

今天,比过去更多的是在研究中讨论抄袭。网络的条件和在短时间内进行复杂和智能搜索的可能性,被评为这一点,并因此给研究带来了重大损害。工具设计来处理抄袭行为的文字和忽略图像。另一方面,信息传递的一个不可分割的部分是图像,在一篇文章或科学研究中传递了大量的信息。由于图像包含的范围非常广泛,特别是在计算机的文本中发现了大量的流程图图像,而且就图像而言,流程图承载着大量的信息,可能成为抄袭的选择之一。本文的目的是利用人工神经网络从流程图图像抄袭的角度考察论文的抄袭率。该方法在结构、节点和边缘方面的平均识别准确率为81.91%,表明该方法是成功的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Plagiarism detection of flowchart images in the texts
Today, much more than in the past are discussed of plagiarism in the research. Conditions of the Web and Possibility of complex and smart searches in a short time, is rated to this, and as a result has arrived significant damages to the research. Tools designed to deal with plagiarism act on the text and ignore images. On the other, an inseparable part of information transfer are images that transfer the large volume of information in an article or scientific research. Because of the images include a very wide range and especially found large amounts of flowchart images in the computer's texts, and as respects, flowcharts are carrying a lot of information, could be one of the options of plagiarism. The purpose of this paper is examine the plagiarism rate of a paper in terms of flowchart images plagiarism using artificial neural network. The average of flowchart images recognition accuracy in terms of structure, nodes and edges in the proposed method with 81.91 percent, indicating the success of this method.
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