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Clustering-Based Searching and Navigation in an Online News Source

  • Simón C. Smith
  • M. Andrea Rodríguez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3936)

Abstract

The growing amount of online news posted on the WWW demands new algorithms that support topic detection, search, and navigation of news documents. This work presents an algorithm for topic detection that considers the temporal evolution of news and the structure of web documents. Then, it uses the results of the topic detection algorithm for searching and navigating in an online news source. An experimental evaluation with a collection of online news in Spanish indicates the advantages of incorporating the temporal aspect and structure of documents in the topic detection of news. In addition, topic-based clusters are well suited for guiding the search and navigation of news.

Keywords

False Alarm Information Retrieval Vector Model Online News Topic Detection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Simón C. Smith
    • 1
  • M. Andrea Rodríguez
    • 1
  1. 1.Department of Computer ScienceUniversity of Concepción, Center for Web Research, University of ChileConcepciónChile

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