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An improved plagiarism detection scheme based on semantic role labeling

机译：一种改进的基于语义角色标记的窃检测方案

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摘要

Plagiarism occurs when the content is copied without permission or citation. One of the contributing factors is that many text documents on the internet are easily copied and accessed. This paper introduces a plagiarism detection technique based on the Semantic Role Labeling (SRL). The technique analyses and compares text based on the semantic allocation for each term inside the sentence. SRL is superior in generating arguments for each sentence semantically. Weighting for each argument generated by SRL to study its behaviour is also introduced in this paper. It was found that not all arguments affect the plagiarism detection process. In addition, experimental results on PAN-PC-09 data sets showed that our method significantly outperforms the modern methods for plagiarism detection in terms of Recall, Precision and F-measure.
机译：未经许可或引用复制内容时，抄袭即会发生。促成因素之一是互联网上的许多文本文档都易于复制和访问。本文介绍了一种基于语义角色标记（SRL）的窃检测技术。该技术基于句子中每个术语的语义分配来分析和比较文本。 SRL在语义上为每个句子生成自变量方面具有优势。本文还介绍了SRL生成的每个参数的权重，以研究其行为。发现并非所有论点都影响affect窃检测过程。此外，在PAN-PC-09数据集上的实验结果表明，在查全率，精确度和F测量方面，我们的方法明显优于现代的the窃检测方法。

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