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Erschienen in:
2014 | OriginalPaper | Buchkapitel
Natural Language Processing for Linking Online News and Open Government Data
verfasst von : Daniel Sarmiento Suárez, Claudia Jiménez-Guarín
Erschienen in: Advances in Conceptual Modeling
Verlag: Springer International Publishing
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The value in the vast amount of linked data and open data produced during the last decade is widely recognized and being exploited by different initiatives. However, a remaining challenge is to integrate government information with semi-structured data in sources relevant to citizens, who have become skeptical of official versions and more interested in information associated with their own interests and values. We present a system that integrates and provides uniform access to government data linked to news portals, via an automated named entity linking process, and information provided by a parliament monitoring organization. We develop a prototype to show how this system can be used to develop semantic web applications that assist citizens in making informed political decisions using data linked to their interests and sources not affiliated with the government. This enables them to contrast the official information and find political figures associated to their own personal interests.