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. © 2012 Springer-Verlag.
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CITATION STYLE
Silveira, S. B., & Branco, A. (2012). Using a double clustering approach to build extractive multi-document summaries. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7499 LNAI, pp. 298–305). https://doi.org/10.1007/978-3-642-32790-2_36
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