Machine learning tool and meta-heuristic based on genetic algorithms for plagiarism detection over mail service

Hadj Ahmed Bouarara, Amine Rahmani, R. M. Hamou, Abdelmalek Amine
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引用次数: 11

Abstract

One of the most modern problems that computer science try to resolve is the plagiarism, in this article we present a new approach for automatic plagiarism detection in world of mail service. Our system is based on the n-gram character for the representation of the texts and tfidf as weighting to calculate the importance of term in the corpus, we use also a combination between the machine learning methods as a way to detect if a document is plagiarized or not, we use pan 09 corpus for the construction and evaluation of the prediction model then we simulate a meta-heuristic method based on genetic algorithms with a variations of parameters to know if it can improve the results. The main objective of our work is to protect intellectual property and improve the efficiency of plagiarism detection system.
基于遗传算法的邮件剽窃检测机器学习工具和元启发式算法
摘要本文提出了一种用于邮件服务领域的自动抄袭检测的新方法。我们的系统是基于n元字符表示的文本和tfidf作为权重计算语料库词的重要性,我们也使用一个结合机器学习的方法来检测是否剽窃一个文档,我们用锅09语料库的建设和评价预测模型然后我们模拟一个基于遗传算法的变异meta-heuristic方法参数来知道它可以改善结果。我们工作的主要目的是保护知识产权,提高抄袭检测系统的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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