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  4. A crowdsourcing methodology for improved geographic focus identification of news-stories
 
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A crowdsourcing methodology for improved geographic focus identification of news-stories

Author(s)
Rodosthenous C.
Michael, Loizos 
Date Issued
2021
Page Start
680
Page End
687
DOI
10.5220/0010228406800687
Faculty
Faculty of Pure and Applied Sciences 
Abstract
Past work on the task of identifying the geographic focus of news-stories has established that state-of-the-art performance can be achieved by using existing crowdsourced knowledge-bases. In this work we demonstrate that a further refinement of those knowledge-bases through an additional round of crowdsourcing can lead to improved performance on the aforementioned task. Our proposed methodology views existing knowledge-bases as collections of arguments in support of particular inferences in terms of the geographic focus of a given news-story. The refinement that we propose is to associate these arguments with weights - computed through crowdsourcing - in terms of how strongly they support their inference. The empirical results that we present establish the superior performance of this approach compared to the one using the original knowledge-base. � 2021 by SCITEPRESS - Science and Technology Publications, Lda.
Publisher
SciTePress
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