We present an overview of the TREC-COVID Challenge, an information retrieval (IR) shared task to evaluate search on scientific literature related to COVID-19. The goals of TREC-COVID include the construction of a pandemic search test collection and the evaluation of IR methods for COVID-19. The challenge was conducted over five rounds from April to July, 2020, with participation from 92 unique teams and 556 individual submissions. A total of 50 topics (sets of related queries) were used in the evaluation, starting at 30 topics for Round 1 and adding 5 new topics per round to target emerging topics at that state of the still-emerging pandemic. This paper provides a comprehensive overview of the structure and results of TREC-COVID. Specifically, the paper provides details on the background, task structure, topic structure, corpus, participation, pooling, assessment, judgments, results, top-performing systems, lessons learned, and benchmark datasets.

翻译：我们概述了 " TREC-COVID挑战 ",这是一项信息检索(IR)的共同任务,用于评价与COVID-19有关的科学文献的搜索情况。 " TREC-COVID " 的目标包括建立一个大流行病搜索测试库和评估COVID-19的IR方法。这项挑战在2020年4月至7月分五轮进行,有92个独特的小组和556个个人提交材料参加。在评价中共使用了50个专题(相关查询系列),从第1轮的30个专题开始,每轮增加5个新专题,针对仍在不断出现的大流行病状态下出现的新专题。本文全面概述了TREC-COVID的结构和结果。具体地说,该文件详细介绍了背景、任务结构、专题结构、主体、参与、集合、评估、判断、结果、最佳系统、经验教训和基准数据集。