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Event detection from news articles

Sayyadi, H ; Sharif University of Technology | 2008

306 Viewed
  1. Type of Document: Article
  2. DOI: 10.1007/978-3-540-89985-3_148
  3. Publisher: 2008
  4. Abstract:
  5. In this paper, we propose a new method for automatic news event detection. An event is a specific happening in a particular time and place. We propose a new model in this paper to detect news events using a label based clustering approach. The model takes advantage of the fact that news events are news clusters with high internal similarity whose articles are about an event in a specific time and place. Since news articles about a particular event may appear in several consecutive days, we developed this model to be able to distinguish such events and merge the corresponding news articles. Although event detection is propounded as a stand alone news mining task, it has also applications in news articles ranking services. © 2008 Springer-Verlag
  6. Keywords:
  7. Clustering ; Event detection ; News information ; News Mining ; News Ranking ; Computer science ; Information retrieval
  8. Source: 13th International Computer Society of Iran Computer Conference on Advances in Computer Science and Engineering, CSICC 2008, Kish Island, 9 March 2008 through 11 March 2008 ; Volume 6 CCIS , 2008 , Pages 981-984 ; 18650929 (ISSN); 3540899847 (ISBN); 9783540899846 (ISBN)
  9. URL: https://link.springer.com/chapter/10.1007/978-3-540-89985-3_148