论文标题
检测和分析对已发表的科学实体缺失的引用
Detecting and analyzing missing citations to published scientific entities
论文作者
论文摘要
正确的引用在学术写作中非常重要，因为它可以使知识积累并保持学术完整性。但是，正确援引并不是一件容易的事。对于已发表的科学实体，不断增长的学术出版物和过度熟悉的术语很容易导致缺少引用。为了应对这种情况，我们根据已发表的科学实体和以前研究人员相同句子中发表的科学实体与文本引用之间的共发生设计了一种特殊的方法引用建议。实验结果表明，我们方法在推荐已发表的科学实体的源文件方面的有效性。我们进一步对2020年著名计算机科学会议发表的论文中缺少引用的统计分析进行了统计分析。在收集的12,278篇论文中，发现475篇已发表的计算机科学和数学科学实体缺失引用。发现没有引用的许多实体被发现是公认的研究结果。在8年前发表了这些发表的具有缺失的科学实体的论文中间，这些论文被认为是发表的科学实体发展成一个良好接受的概念的时间范围。对于已发表的科学实体，我们呼吁按照学术标准的要求准确，充分引用其源文件。
Proper citation is of great importance in academic writing for it enables knowledge accumulation and maintains academic integrity. However, citing properly is not an easy task. For published scientific entities, the ever-growing academic publications and over-familiarity of terms easily lead to missing citations. To deal with this situation, we design a special method Citation Recommendation for Published Scientific Entity (CRPSE) based on the cooccurrences between published scientific entities and in-text citations in the same sentences from previous researchers. Experimental outcomes show the effectiveness of our method in recommending the source papers for published scientific entities. We further conduct a statistical analysis on missing citations among papers published in prestigious computer science conferences in 2020. In the 12,278 papers collected, 475 published scientific entities of computer science and mathematics are found to have missing citations. Many entities mentioned without citations are found to be well-accepted research results. On a median basis, the papers proposing these published scientific entities with missing citations were published 8 years ago, which can be considered the time frame for a published scientific entity to develop into a well-accepted concept. For published scientific entities, we appeal for accurate and full citation of their source papers as required by academic standards.
