论文标题
通过在COVID-19本体论中进行推理，检测新的冠状病毒的假新闻
Detecting fake news for the new coronavirus by reasoning on the Covid-19 ontology
论文作者
论文摘要
在COVID-19大流行的背景下，许多人很快传播欺骗性信息。我在这里调查描述逻辑（DLS）中的推理如何检测可信赖的医疗来源和不信任的逻辑之间的不一致。未经信任的信息是自然语言（例如，“ Covid-19仅影响老年人”）。要自动转换为DLS，我使用了FRED转换器。然后使用Racer工具执行描述逻辑中的推理。
In the context of the Covid-19 pandemic, many were quick to spread deceptive information. I investigate here how reasoning in Description Logics (DLs) can detect inconsistencies between trusted medical sources and not trusted ones. The not-trusted information comes in natural language (e.g. "Covid-19 affects only the elderly"). To automatically convert into DLs, I used the FRED converter. Reasoning in Description Logics is then performed with the Racer tool.
