论文标题
搜索科学文献以获取有关COVID-19问题的答案
Searching Scientific Literature for Answers on COVID-19 Questions
论文作者
论文摘要
随着新信息逐渐获得，找到与新型疾病大流行有关的答案为寻求和检索带来了新的挑战。 TREC COVID搜索轨道旨在帮助创建搜索工具，以帮助科学家，临床医生，决策者和其他具有相似信息需求的人，以从科学文献中找到可靠的答案。作为参与这一挑战的一部分，我们尝试了不同的排名算法。我们提出了一种新颖的神经检索方法，并证明了其对TREC搜索的有效性。
Finding answers related to a pandemic of a novel disease raises new challenges for information seeking and retrieval, as the new information becomes available gradually. TREC COVID search track aims to assist in creating search tools to aid scientists, clinicians, policy makers and others with similar information needs in finding reliable answers from the scientific literature. We experiment with different ranking algorithms as part of our participation in this challenge. We propose a novel method for neural retrieval, and demonstrate its effectiveness on the TREC COVID search.
