Browsing by Subject "Multi-document summarization"
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Item Open Access Cover coefficient-based multi-document summarization(Springer, 2009-04) Ercan, Gönenç; Can, FazlıIn this paper we present a generic, language independent multi-document summarization system forming extracts using the cover coefficient concept. Cover Coefficient-based Summarizer (CCS) uses similarity between sentences to determine representative sentences. Experiments indicate that CCS is an efficient algorithm that is able to generate quality summaries online. © Springer-Verlag Berlin Heidelberg 2009.Item Open Access Semantic argument frequency-based multi-document summarization(IEEE, 2009-09) Aksoy, Cem; Buğdaycı, Ahmet; Gür, Tunay; Uysal, İbrahim; Can, FazlıSemantic Role Labeling (SRL) aims to identify the constituents of a sentence, together with their roles with respect to the sentence predicates. In this paper, we introduce and assess the idea of using SRL on generic Multi-Document Summarization (MDS). We score sentences according to their inclusion of frequent semantic phrases and form the summary using the top-scored sentences. We compare this method with a term-based sentence scoring approach to investigate the effects of using semantic units instead of single words for sentence scoring. We also integrate our scoring metric as an auxiliary feature to a cutting edge summarizer with the intention of examining its effects on the performance. The experiments using datasets from the Document Understanding Conference (DUC) 2004 show that the SRL-based summarization outperforms the term-based approach as well as most of the DUC participants. © 2009 IEEE.