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

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.

• Type: Conference
• Year: 2007
• Where: ACL
• Authors: María Fuentes Fort, Enrique Alfonseca, Horacio Rodríguez
• Keywords: ACL 2007, Computational Linguistics, Several SVMs, Summary Content Units, Support Vector Machines