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Retrieving Candidate Plagiarised Documents Using Query Expansion

机译:使用查询扩展检索Pla窃的候选文档

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External plagiarism detection systems compare suspicious texts against a reference collection to identify the original one(s). The suspicious text may not contain a verbatim copy of the reference collection since plagiarists often try to disguise their behaviour by altering the text. For large reference collections, such as those accessible via the internet, it is not practical to compare the suspicious text with every document in the reference collection. Consequently many approaches to plagiarism detection begin by identifying a set of candidate documents from the reference collection. We report an IR-based approach to the candidate document selection problem that uses query expansion to identify candidates which have been altered. The reported system outperforms a previously reported approach and is also robust to changes in the reference collection text.
机译:外部窃检测系统将可疑文本与参考集合进行比较,以识别原始文本。可疑文本可能不包含参考文献的逐字记录副本,因为窃者经常试图通过更改文本来掩饰其行为。对于大型参考馆藏,例如可通过互联网访问的参考馆藏,将可疑文本与参考馆藏中的每个文档进行比较是不切实际的。因此,many窃检测的许多方法都是从参考集合中识别出一组候选文档开始的。我们报告了一种基于IR的候选文档选择问题的方法,该方法使用查询扩展来识别已更改的候选对象。报告的系统优于以前报告的方法,并且对于参考集合文本的更改也很健壮。

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