与学术剽窃的斗争：基于语义相似性的方法
The Struggle with Academic Plagiarism: Approaches based on Semantic Similarity
摘要：
学术剽窃是当今一个严重的问题。由于存在取之不尽用之不竭的数字信息来源，今天比以往任何时候都更容易抄袭。好的一面是，剽窃检测技术已经得到了改进，并且足够强大，可以检测出教育领域的剽窃企图。我们现在正在见证高效的剽窃检测软件，如Turnitin，iThenticate或SafeAssign。在引言中，我们探讨了在克罗地亚学术界用于大学和/或科学期刊中剽窃检测的软件。问题是：这是否足够？目前的软件已经被证明是成功的，但是识别释义或混淆剽窃的问题仍然没有解决。在本文中，我们提出了一份报告，如何语义相似性的措施，可以用于剽窃检测任务。
英文摘要：
Academic plagiarism is a serious problem nowadays. Due to the existence of inexhaustible sources of digital information, today it is easier to plagiarize more than ever before. The good thing is that plagiarism detection techniques have improved and are powerful enough to detect attempts of plagiarism in education. We are now witnessing efficient plagiarism detection software in action, such as Turnitin, iThenticate or SafeAssign. In the introduction we explore software that is used within the Croatian academic community for plagiarism detection in universities and/or in scientific journals. The question is: is this enough? Current software has proven to be successful, however the problem of identifying paraphrasing or obfuscation plagiarism remains unresolved. In this paper we present a report of how semantic similarity measures can be used in the plagiarism detection task.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
