Abstract
In this paper we propose an effective method to summarize document clusters. This method is based on the Testor Theory, and it is applied to a group of newspaper articles in order to summarize the events that they describe. This method is also applicable to either a very large document collection or a very large document, in order to identify the main themes (topics) of the collection (documents) and to summarize them. The results obtained in the experiments demonstrate the usefulness of the proposed method.
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Pons-Porrata, A., Ruiz-Shulcloper, J., Berlanga-Llavori, R. (2003). A Method for the Automatic Summarization of Topic-Based Clusters of Documents. In: Sanfeliu, A., Ruiz-Shulcloper, J. (eds) Progress in Pattern Recognition, Speech and Image Analysis. CIARP 2003. Lecture Notes in Computer Science, vol 2905. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24586-5_73
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DOI: https://doi.org/10.1007/978-3-540-24586-5_73
Publisher Name: Springer, Berlin, Heidelberg
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