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Generating Semantic Snapshots of Newscasts Using Entity Expansion

  • José Luis Redondo GarcíaEmail author
  • Giuseppe Rizzo
  • Lilia Perez Romero
  • Michiel Hildebrand
  • Raphaël Troncy
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9114)

Abstract

TV newscasts report about the latest event-related facts occurring in the world. Relying exclusively on them is, however, insufficient to fully grasp the context of the story being reported. In this paper, we propose an approach that retrieves and analyzes related documents from the Web to automatically generate semantic annotations that provide viewers and experts comprehensive information about the news. We detect named entities in the retrieved documents that further disclose relevant concepts that were not explicitly mentioned in the original newscast. A ranking algorithm based on entity frequency, popularity peak analysis, and domain experts’ rules sorts those annotations to generate what we call Semantic Snapshot of a Newscast (NSS). We benchmark this method against a gold standard generated by domain experts and assessed via a user survey over five BBC newscasts. Results of the experiments show the robustness of our approach holding an Average Normalized Discounted Cumulative Gain of 66.6%.

Keywords

Semantic Video Annotation Entity expansion Newscasts 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • José Luis Redondo García
    • 1
    Email author
  • Giuseppe Rizzo
    • 1
  • Lilia Perez Romero
    • 2
  • Michiel Hildebrand
    • 2
  • Raphaël Troncy
    • 1
  1. 1.EURECOMSophia AntipolisFrance
  2. 2.CWIAmsterdamThe Netherlands

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