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Semantic metadata annotation: tagging medline abstracts for enhanced information access

Authors: Ibekwe, Fidelia;

Semantic metadata annotation: tagging medline abstracts for enhanced information access

Abstract

The object of this study is to develop methods for automatically annotating the argumentative role of sentences in scientific abstracts. Working from Medline abstracts, we classified sentences into four major argumentative roles: objective, method, result, conclusion. The idea is that if the role of each sentence can be marked up, then this metadata can be used during information retrieval to seek for particular types of information such as novelty, conclusions, methodologies, aims/goals of a scientific piece of work.

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Keywords

argumentative role, sentence classification, https://iskouk.org/subjects/W50L1KJK, https://iskouk.org/subjects/PHP2YCSR, https://iskouk.org/subjects/XPBRH3E0, biomedical abstracts, discourse analysis, semantic metadata annotation, https://iskouk.org/subjects/Q4L57KRN, https://iskouk.org/subjects/TH68G7W5

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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