Deep distributed news: ontologies to the rescue of journalism

  • Authors:
  • Alexandre Cayla-Irigoyen;Esma Aïmeur

  • Affiliations:
  • Department of Computer Science and Operations Research, University of Montreal, Québec, Canada;Department of Computer Science and Operations Research, University of Montreal, Québec, Canada

  • Venue:
  • AI'10 Proceedings of the 23rd Canadian conference on Advances in Artificial Intelligence
  • Year:
  • 2010

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Abstract

New media such as the Internet has greatly expanded the informational horizons of news consumers However, it has brought about its own set of problems such as information overload In this paper, we suggest that the semantic web is the best means to help news consumers regain control of the news We posit that by modeling the environment in which social activity takes place (and news events take place) it is possible to clarify the links between news items and the general context Additionally, by comparing this model to the user's own conceptualization, news content could be adapted to better fit his or her needs We call this theoretical model Deep Distributed News.