Entity summarization of news articles

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 entitylabeled 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. Categories and Subject Descriptors: H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval General Terms: Algorithms, Measurement, Experimentation

• Type: Conference
• Year: 2010
• Where: SIGIR
• Authors: Gianluca Demartini, Malik Muhammad Saad Missen, Roi Blanco, Hugo Zaragoza
• Keywords: Entity Retrieval, Information Technology, Relevant Entities, Retrieval General Terms, SIGIR 2010