摘要：

【目的】高效识别洗稿学术论文,防范此类学术不端行为,提高科技期刊办刊质量。【方法】分析洗稿原理,收集洗稿测试数据,比较样本原文和洗稿成品的异同;利用人工智能服务平台和中国知网网站,有针对性地探索出基于关键词提取和比对的技术性方法。【结果】按提出的方法测试数个样本后,发现该方法能较准确地识别出洗稿学术论文。【结论】提出的识别洗稿学术论文的方法具初步有效性。待学术期刊编辑人员广泛测试,验证该方法的有效性后,可将该方法软件化或平台化,以利编辑人员日常使用。

关键词: 洗稿, 人工智能, 自然语言处理, 关键词, 文本相似性, 学术不端, 学术论文

Abstract:

[Purposes] This paper aims to identify the spun academic papers efficiently, prevent such academic misconduct, and improve the quality of scientific journals. [Methods] We analyzed the principles of paper spinning, collected data on paper spinning tests, and compared the similarities and differences between the original sample and the finished spun paper. By using the artificial intelligence service platform and the China National Knowledge Infrastructure website, we explored technical methods based on keyword extraction and comparison. [Findings] After testing several samples by the proposed method, it is found that the method can accurately identify the spun academic papers. [Conclusions] The proposed method has initial validity in identifying the spun academic papers. After the editors of academic journals widely test and verify the effectiveness of this method, this method can be software-based or platform-based to facilitate the daily use of editors.

Key words: Paper spinning, Artificial intelligence, Natural language processing, Keyword, Text similarity, Academic misconduct, Academic paper