Abstract
This paper presents a method for extractive multi-document summarization that explores a two-phase clustering approach. First, sentences are clustered by similarity, and one sentence per cluster is selected, to reduce redundancy. Then, in order to group them according to topics, those sentences are clustered considering the collection of keywords that represent the topics in the set of texts. Evaluation reveals that the approach pursued produces highly informative summaries, containing many relevant data and no repeated information.
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Silveira, S.B., Branco, A. (2012). Using a Double Clustering Approach to Build Extractive Multi-document Summaries. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2012. Lecture Notes in Computer Science(), vol 7499. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32790-2_36
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DOI: https://doi.org/10.1007/978-3-642-32790-2_36
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