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Plagiarism Detection Using Machine Learning-Based Paraphrase Recognizer

机译:使用基于机器学习的复述识别器进行窃检测

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摘要

Plagiarism in free text has become a common occurrence due to the wide availability of voluminous information resources. Automatic plagiarism detection systems aim to identify plagiarized content present in large repositories. This task is rendered difficult by the use of sophisticated plagiarism techniques such as paraphrasing and summarization, which mask the occurrence of plagiarism. In this work, a monolingual plagiarism detection technique has been developed to tackle cases of paraphrased plagiarism. A support vector machine based paraphrase recognition system, which works by extracting lexical, syntactic, and semantic features from input text has been used. Both sentence-level and passage-level approaches have been investigated. The performance of the system has been evaluated on various corpora, and the passage level approach has registered promising results.
机译:由于大量信息资源的广泛可用性,自由文本中的窃已成为一种普遍现象。自动窃检测系统旨在识别大型存储库中存在的窃内容。通过使用复杂的抄袭技术(例如,措辞和摘要)掩盖了of窃的发生,使这项任务变得困难。在这项工作中,已经开发出一种单语窃检测技术来解决释义窃的案例。使用了一种基于支持向量机的释义识别系统,该系统通过从输入文本中提取词汇,句法和语义特征来工作。句子级别和段落级别的方法都已被研究。该系统的性能已在各种语料库上进行了评估,并且通过级别方法已取得了可喜的结果。

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