Support Vector Machines for Query-focused Summarization trained and evaluated on Pyramid data
نویسندگان
چکیده
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.
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