Presenter(s)

    Matthew A Weiler

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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 project

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

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