Work

Comparable Study of Event Extraction in Newswire and Biomedical Domains

Year: 2014

Type: conference-paper

Abstract: Event extraction is a popular research topic in natural language processing.Several event extraction tasks have been defined for both the newswire and biomedical domains.In general, different systems have been developed for the two domains, despite the fact that the tasks in both domains share a number of characteristics.In this paper, we analyse the commonalities and differences between the tasks in the two domains.Based on this analysis, we demonstrate how an event extraction method originally designed for the biomedical domain can be adapted for application to the newswire domain.The performance is state-of-the-art for both domains, with F-scores of 52.7% for the biomedical domain and 52.1% for the newswire domain in terms of their primary evaluation metrics.

Source: Research Explorer (The University of Manchester)

Authors: Makoto Miwa, Paul M. Thompson, Ioannis Korkontzelos, Sophia Ananiadou

Institutions: The University of Tokyo, University of Manchester

Language: English

Topic: Topic Modeling

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: European Commission, Arts and Humanities Research Council, Medical Research Council, Japan Society for the Promotion of Science

Awards: Mining the History of Medicine, Automated Measurement and Analysis of Open Source Software, Wide-coverage event extraction from biomedical texts, Supporting Evidence-based Public Health Interventions using Text Mining

OpenAlex ID: W2251658646