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.
CitationFuentes, 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.
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