2010 IdentifyingTheInfStructOfSciAbstracts

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Subject Headings: Scientific Paper Abstract, Scientific Paper.

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Quotes

Abstract

  • Many practical tasks require accessing specific types of information in scientific literature; e.g. information about the objective, methods, results or conclusions of the study in question. Several schemes have been developed to characterize such information in full journal papers. Yet many tasks focus on abstracts instead. We take three schemes of different type and granularity (those based on section names, argumentative zones and conceptual structure of documents) and investigate their applicability to biomedical abstracts. We show that even for the finest-grained of these schemes, the majority of categories appear in abstracts and can be identified relatively reliably using machine learning. We discuss the impact of our results and the need for subsequent task-based evaluation of the schemes.

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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2010 IdentifyingTheInfStructOfSciAbstractsAnna Korhonen
Maria Liakata
Yufan Guo
Ilona Silins
Lin Sun
Ulla Stenius		Identifying the Information Structure of Scientific Abstracts: An Investigation of Three Different SchemesProceedings of the BioNLP Workshop on Linking Natural Language Processing and Biologyhttp://www.aclweb.org/anthology/W/W10/W10-1913.pdf2010
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