Automatic Simplification of Scientific Texts: SimpleText Lab at CLEF-2022

Autor: Ermakova, L., Bellot, P., Kamps, J., Nurbakova, D., Ovchinnikova, I., SanJuan, E., Mathurin, E., Araújo, S., Hannachi, R., Huet, S., Poinsu, N., Hagen, M., Verberne, S., Macdonald, C., Seifert, C., Balog, K., Nørvåg, K., Setty, V.
Přispěvatelé: Héritages et Constructions dans le Texte et l'Image (HCTI), Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Institut Brestois des Sciences de l'Homme et de la Société (IBSHS), Université de Brest (UBO), Laboratoire d'Informatique et Systèmes (LIS), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), University of Amsterdam [Amsterdam] (UvA), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA), Laboratoire Informatique d'Avignon (LIA), Avignon Université (AU)-Centre d'Enseignement et de Recherche en Informatique - CERI, Universidade do Minho = University of Minho [Braga], Héritage et Création dans le Texte et l'Image (HCTI), Université de Brest (UBO)-Université de Bretagne Occidentale, ILLC (FGw)
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Lecture Notes in Computer Science ISBN: 9783030997380
44th European Conference on Information Retrieval (ECIR)
44th European Conference on Information Retrieval (ECIR), Apr 2022, Stavanger, France. pp.364-373, ⟨10.1007/978-3-030-99739-7_46⟩
Advances in Information Retrieval: 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022 : proceedings, II, 364-373
ISSN: 0302-9743
DOI: 10.1007/978-3-030-99739-7_46
Popis: The Web and social media have become the main source of information for citizens, with the risk that users rely on shallow information in sources prioritizing commercial or political incentives rather than the correctness and informational value. Non-experts tend to avoid scientific literature due to its complex language or their lack of prior background knowledge. Text simplification promises to remove some of these barriers. The CLEF 2022 SimpleText track addresses the challenges of text simplification approaches in the context of promoting scientific information access, by providing appropriate data and benchmarks, and creating a community of NLP and IR researchers working together to resolve one of the greatest challenges of today. The track will use a corpus of scientific literature abstracts and popular science requests. It features three tasks. First, content selection (what is in, or out?) challenges systems to select passages to include in a simplified summary in response to a query. Second, complexity spotting (what is unclear?) given a passage and a query, aims to rank terms/concepts that are required to be explained for understanding this passage (definitions, context, applications). Third, text simplification (rewrite this!) given a query, asks to simplify passages from scientific abstracts while preserving the main content.
Databáze: OpenAIRE
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