Inferring the Geographic Focus of Stories Using Crowdsourced Knowledge Bases
Published in Cognition and Artificial Intelligence for Human-Centred Design (CAID2017), 2017
We consider the problem of identifying the geographic focus of a story and more specifically a news story. Most of the times, we do not expect the story to explicitly mention the target region, making our problem one of inference or prediction, rather than one of identification. Further, we seek to tackle the problem without appealing to specialized geographic information resources like gazetteers or atlases, but employ only general-purpose crowdsourced knowledge bases and ontologies like ConceptNet and YAGO and techniques that are cognitively compatible with human reasoning. In particular, we propose certain natural strategies towards addressing the problem, and show that the GeoMantis system that implements these strategies outperforms an existing state-of-the-art system, when compared on stories whose target region (country, in particular) is not explicitly mentioned or is obscured. Our results give evidence that using general-purpose crowdsourced knowledge bases and ontologies can, in certain cases, outperform even specialized tools.
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Cite this work: Christos Rodosthenous, Loizos Michael, "Inferring the Geographic Focus of Stories Using Crowdsourced Knowledge Bases." Cognition and Artificial Intelligence for Human-Centred Design (CAID2017), 2017.