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. © Springer-Verlag Berlin Heidelberg 2006.
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CITATION STYLE
Smith, S. C., & Rodríguez, M. A. (2006). Clustering-based searching and navigation in an online news source. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3936 LNCS, pp. 143–154). Springer Verlag. https://doi.org/10.1007/11735106_14
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