Ontology-based and User-focused Automatic Text Summarization (OATS): Using COVID-19 Risk Factors as an Example
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.
Code (0)
등록된 구현이 없습니다.
Tasks
Question AnsweringText SummarizationSimilar Papers 제목 키워드 기반
Query-Focused Extractive Video Summarization
Video data is explosively growing. As a result of the "big video data", intelligent algorithms for automatic video summarization have re-emerged as a pressing need. We develop a probabilistic model, Sequential and Hierar…
Query focused video summarizationVideo SummarizationThe State and Fate of Summarization Datasets
Automatic summarization has consistently attracted attention, due to its versatility and wide application in various downstream tasks. Despite its popularity, we find that annotation efforts have largely been disjointed,…
CLIP-It! Language-Guided Video Summarization
A generic video summary is an abridged version of a video that conveys the whole story and features the most important scenes. Yet the importance of scenes in a video is often subjective, and users should have the option…
Query-focused SummarizationQuery focused video summarizationSupervised Video SummarizationVideo SummarizationQuery-Focused Opinion Summarization for User-Generated Content
We present a submodular function-based framework for query-focused opinion summarization. Within our framework, relevance ordering produced by a statistical ranker, and information coverage with respect to topic distribu…
DiversityOpinion Summarizationtext similarityMachine Learning of Generic and User-Focused Summarization
A key problem in text summarization is finding a salience function which determines what information in the source should be included in the summary. This paper describes the use of machine learning on a training corpus …
BIG-bench Machine LearningText Summarization