  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.
