BioNex: A System For Biomedical News Event Exploration

authored by

Patrick Ernst, Arunav Mishra, Avishek Anand, Vinay Setty

Abstract

We demonstrate BioNex, a system to mine, rank and visualize biomedical news events. BioNex takes biomedical queries such as "Ebola virus disease" and retrieves the k most relevant news events for them. To achieve this we first mine the generic news events by clustering them on a daily basis using general named entities and textual features. These clusters are also tagged with disambiguated biomedical entities which aid in biomedical news event exploration. These clusters are then used to compute the importance scores for the event clusters based on a combination of textual, semantic, popularity and historical importance features. BioNex also visualizes the retrieved event clusters to highlight the top news events and corresponding news articles for the given query. The visualization also provides the context for news events using (1) a chain of historically relevant news event clusters, and (2) other non-biomedical events from the same day.

Organisation(s)

L3S Research Centre

External Organisation(s)

Max-Planck Institute for Informatics
Aalborg University

Type

Conference contribution

Pages

1277-1280

No. of pages

4

Publication date

2017

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Information Systems, Software, Computer Graphics and Computer-Aided Design

Sustainable Development Goals

SDG 3 - Good Health and Well-being

Electronic version(s)

https://doi.org/10.1145/3077136.3084150 (Access: Closed)