论文标题
基于本体的和以用户为中心的自动文本摘要（OATS）：以COVID-19的风险因素为例
Ontology-based and User-focused Automatic Text Summarization (OATS): Using COVID-19 Risk Factors as an Example
论文作者
论文摘要
本文提出了一个基于本体的新颖和以用户为中心的自动文本摘要（OATS）系统，在目标的环境中，通过提取包含与用户焦点相符的信息来自动从非结构化文本中自动生成文本摘要。燕麦由两个模块组成：基于本体的主题识别和以用户为中心的文本摘要；它首先利用基于本体的方法来识别相关文档以引起用户的兴趣，然后利用从用户指定的问题中提取的答案，从一个问题回答模型中提取的答案，以生成文本摘要。为了支持与COVID-19的大流行的斗争，我们使用COVID-19风险因素作为一个例子来证明拟议的燕麦系统，目的是帮助医学界准确地识别相关的科学文献并有效地审查了与Covid-19有关的风险因素的信息。
This paper proposes a novel Ontology-based and user-focused Automatic Text Summarization (OATS) system, in the setting where the goal is to automatically generate text summarization from unstructured text by extracting sentences containing the information that aligns to the user's focus. OATS consists of two modules: ontology-based topic identification and user-focused text summarization; it first utilizes an ontology-based approach to identify relevant documents to user's interest, and then takes advantage of the answers extracted from a question answering model using questions specified from users for the generation of text summarization. To support the fight against the COVID-19 pandemic, we used COVID-19 risk factors as an example to demonstrate the proposed OATS system with the aim of helping the medical community accurately identify relevant scientific literature and efficiently review the information that addresses risk factors related to COVID-19.
