Closed-domain event extraction for hard news event monitoring: a systematic study.

ABSTRACT: News event monitoring systems allow real-time monitoring of a large number of events reported in the news, including the urgent and critical events comprising the so-called hard news. These systems heavily rely on natural language processing (NLP) to perform automatic event extraction at scale. While state-of-the-art event extraction models are readily available, integrating them into a news event monitoring system is not as straightforward as it seems due to practical issues related to model selection, robustness, and scale. To address this gap, we present a study on the practical use of event extraction models for news event monitoring. Our study focuses on the key task of closed-domain main event extraction (CDMEE), which aims to determine the type of the story's main event and extract

SUBMITTER: Dukic D 

PROVIDER: S-EPMC11623237 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature