AbuRa'ed, Ahmed Ghassan TawfiqChiruzzo, LuisSaggion, HoracioAccuosto, PabloBravo Serrano, Àlex, 1984-2017-10-052017-10-052017Abura'ed A, Chiruzzo L, Saggion H, Accuosto P, Bravo A. LaSTUS/TALN @ CLSciSumm-17: cross-document sentence matching and scientific text summarization systems. In: Jaidka K, Chandrasekaran MK, Kan MY. Proceedings of the Computational Linguistics Scientific Summarization Shared Task (CL-SciSumm 2017); 2017 Aug 11; Tokyo, Japan. [Aachen]: CEUR-WS; 2017. p. 55-66.1613-0073http://hdl.handle.net/10230/32857Comunicació presentada a: CL-SciSumm 2017, organitzat com a part de The 2nd Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL 2017) i conjuntament amb The 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2017)In recent years there has been an increasing interest in approaches to scienti c summarization that take advantage of the citations a research paper has received in order to extract its main contributions. In this context, the CL-SciSumm 2017 Shared Task has been proposed to address citation-based information extraction and summarization. In this paper we present several systems to address three of the CL-SciSumm tasks. Notably, unsupervised systems to match citing and cited sentences (Task 1A), a supervised approach to identify the type of information being cited (Task 1B), and a supervised citation-based summarizer (Task 2).application/pdfengCopyright © 2017 the authors.info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/openAccess