An Empirical Assessment of Citation Information in Scientific Summarization

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9612)

Abstract

Considering the recent substantial growth of the publication rate of scientific results, nowadays the availability of effective and automated techniques to summarize scientific articles is of utmost importance. In this paper we investigate if and how we can exploit the citations of an article in order to better identify its relevant excerpts. By relying on the BioSumm2014 dataset, we evaluate the variation in performance of extractive summarization approaches when we consider the citations to extend or select the contents of an article to summarize. We compute the maximum ROUGE-2 scores that can be obtained when we summarize a paper by considering its contents together with its citations. We show that the inclusion of citation-related information brings to the generation of better summaries.

Keywords

Citation-based summarization Scientific text mining Summary evaluation 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Natural Language Processing GroupUniversitat Pompeu FabraBarcelonaSpain

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