This paper presents the use of Support
Vector Machines (SVM) to detect relevant
information to be included in a queryfocused
summary. Several SVMs are trained using information from pyramids of summary content units. Their performance is compared with the best performing systems in DUC-2005, using both ROUGE and autoPan, an automatic scoring method for pyramid evaluation.
CitationFuentes, M.; Alfonseca, E.; Rodriguez, H. Support vector machines for query-focused summarization trained and evaluated on pyramid data. A: Annual Meeting of the Association for Computational Linguistics. "45th Annual Meeting of the Association for Computational Linguistics". Praga: 2007, p. 57-60.
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