FEMsum at DUC 2006: Semantic-based approach integrated in a Flexible Eclectic Multitask Summarizer Architecture

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RECERCAT Home > Universitat Politècnica de Catalunya > Documents de recerca > View document

To access the full text documents, please follow this link: http://hdl.handle.net/2117/11336

dc.contributor	Universitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics
dc.contributor	Universitat Politècnica de Catalunya. GPLN - Grup de Processament del Llenguatge Natural
dc.contributor.author	Fuentes Fort, Maria
dc.contributor.author	Rodríguez Hontoria, Horacio
dc.contributor.author	Turmo Borras, Jorge
dc.contributor.author	Ferrés Domènech, Daniel
dc.date	2006
dc.identifier.citation	Fuentes, M. [et al.]. FEMsum at DUC 2006: Semantic-based approach integrated in a flexible eclectic multitask summarizer architecture. A: North American Chapter of the Association for Computational Linguistics - Human Language Technologies. "North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL-HLT 2006)". Brooklyn, Nova York: 2006, p. 1-8.
dc.identifier.uri	http://hdl.handle.net/2117/11336
dc.language.iso	eng
dc.relation	http://www.lsi.upc.edu/~mfuentes/cgi-bin/articles_presentacions/duc06-frtf-8def.pdf
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Llenguatge natural
dc.subject	Natural language processing (Computer science) -- Research
dc.subject	Computational linguistics
dc.subject	DUC 2006
dc.subject	FEMsum
dc.subject	Lingüística computacional
dc.subject	Llenguatge natural (Informàtica) -- Processament
dc.title	FEMsum at DUC 2006: Semantic-based approach integrated in a Flexible Eclectic Multitask Summarizer Architecture
dc.type	info:eu-repo/semantics/submittedVersion
dc.type	info:eu-repo/semantics/conferenceObject
dc.description.abstract	In order to face different requirements at TALP Research Center we have built a highly parameterized environment allowing to instantiate specific summarizers for different summarization tasks in different languages. This paper describes and analyzes how our system deals with the DUC 2006 task of providing summary-length answers to complex questions. The given query is used to detect relevant passages. After that, semantic similarities between these relevant sentences are detected and then used as input of an iterative graph-based algorithm to avoid redundancy and obtain a cohesioned text. NIST human evaluations are used to analyze several aspects of our system and a specific analysis for each of the three different kinds of submitted summaries is reported.
dc.description.abstract	Peer Reviewed

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