Title: Online News Event Extraction for Global Crisis Surveillance
Citation: Transactions on Computational Collective Intelligence vol. 6910 p. 182-212
Publisher: Springer-Verlag
Publication Year: 2011
JRC N°: JRC66720
URI: http://www.springerlink.com/content/k0r755214vw57183/
DOI: 10.1007/978-3-642-24016-4_10
Type: Articles in periodicals and books
Abstract: This article presents a real-time and multilingual news event extraction system developed at the Joint Research Centre of the Euro- pean Commission. It is capable of accurately and efficiently extracting violent and natural disaster events from online news. In particular, a linguistically relatively lightweight approach is deployed, in which clus- tered news are heavily exploited at all stages of processing. Furthermore, the technique applied for event extraction assumes the inverted-pyramid style of writing news articles, i.e., the most important parts of the story are placed in the beginning and the least important facts are left to- ward the end. The article focuses on the system’s architecture, real-time news clustering, geo-locating and geocoding clusters, event extraction grammar development, adapting the system to the processing of new languages, cluster-level information fusion, visual event tracking, event extraction accuracy evaluation, and detecting event reporting boundaries in news article streams. This article is an extended version of [20].
JRC Directorate:Space, Security and Migration

Files in This Item:
There are no files associated with this item.

Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.