Title:
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Support vector machines for query-focused summarization trained and evaluated on pyramid data
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Author:
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Fuentes Fort, Maria; Alfonseca, Enrique; Rodríguez Hontoria, Horacio
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Other authors:
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Universitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics; Universitat Politècnica de Catalunya. GPLN - Grup de Processament del Llenguatge Natural |
Abstract:
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This paper presents the use of Support Vector Machines (SVM) to detect relevant information to be included in a queryfocused summary. Several classifiers are trained using pyramids of summary content
units information. The Mapping-Convergence algorithm is used with positive, unlabeled data, and a small set of negative seeds.
The SVMs are tested on two Document Understanding Conference (DUC) 2006 systems. The performance of the new approaches is compared with the original systems using the DUC 2005 corpus as
test data. For evaluation purposes, we also present an automatic method based on pyramid data with good correlation with other human or automatic procedures. |
Subject(s):
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-Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic -Text summarization -Machine learning |
Rights:
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Document type:
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Article - Published version Report |
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