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Description

In the world today, there is a lack of useful and quality approaches to structuring and semantically annotating data-sets from real-time news outlets. This research represents an essential pipeline and implementation to such a problem and includes background data modeling, event and entity annotation, and finally interlinking events from real-time sources such as twitter headline news sources.

Publication Date

4-18-2018

Project Designation

Graduate Research

Primary Advisor

Saverio Perugini, Saeedeh Shekarpour

Primary Advisor's Department

Computer Science

Keywords

Stander Symposium poster

Comments

Presenter: Matthew A Weiler

HeadEx: ​Real-time Event Extraction and Interlinking from News Headline​s

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