抄袭检测支持工具的测试
Testing of Support Tools for Plagiarism Detection
AI总结：
针对人们对抄袭检测软件的效果预期，测试15款网页端文本匹配系统，经多语言多场景测试发现其存在漏检和误检问题。
摘要：
人们普遍认为，软件必定能轻松完成人类觉得困难的任务。由于查找文本中抄袭的来源并非易事，因此人们普遍预期软件判断文本是否抄袭应该很简单。软件无法判定抄袭，但可以作为支持工具，识别可能构成抄袭的部分文本相似性。但各类系统的实际效果如何呢？本文报告了对15款可在疑似抄袭时使用的基于网络的文本匹配系统的协作测试结果。该测试由来自7个国家的研究人员开展，使用8种不同语言的测试材料，评估了系统在单源和多源文档上的有效性，还进行了可用性检查。令人警醒的结果显示，尽管部分系统确实能帮助识别一些抄袭内容，但它们显然无法找出所有抄袭内容，有时还会将非抄袭材料标记为有问题。
英文摘要：
There is a general belief that software must be able to easily do things that humans find difficult. Since finding sources for plagiarism in a text is not an easy task, there is a wide-spread expectation that it must be simple for software to determine if a text is plagiarized or not. Software cannot determine plagiarism, but it can work as a support tool for identifying some text similarity that may constitute plagiarism. But how well do the various systems work? This paper reports on a collaborative test of 15 web-based text-matching systems that can be used when plagiarism is suspected. It was conducted by researchers from seven countries using test material in eight different languages, evaluating the effectiveness of the systems on single-source and multi-source documents. A usability examination was also performed. The sobering results show that although some systems can indeed help identify some plagiarized content, they clearly do not find all plagiarism and at times also identify non-plagiarized material as problematic.
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。
