Entity summarization of news articles

  • Authors:
  • Gianluca Demartini;Malik Muhammad Saad Missen;Roi Blanco;Hugo Zaragoza

  • Affiliations:
  • L3S Research Center, Hannover, Germany;IRIT , Toulouse, France;Yahoo! Research, Barcelona, Spain;Yahoo! Research, Barcelona, Spain

  • Venue:
  • Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
  • Year:
  • 2010

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Abstract

In this paper we study the problem of entity retrieval for news applications and the importance of the news trail history (i.e. past related articles) to determine the relevant entities in current articles. We construct a novel entity-labeled corpus with temporal information out of the TREC 2004 Novelty collection. We develop and evaluate several features, and show that an article's history can be exploited to improve its summarization.