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Information extraction from full text scientific articles: Where are the keywords?

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Item Type:Article
Title:Information extraction from full text scientific articles: Where are the keywords?
Creators Name:Shah, P. and Perez-Iratxeta, C. and Bork, P. and Andrade, M.A.
Abstract:BACKGROUND: To date, many of the methods for information extraction of biological information from scientific articles are restricted to the abstract of the article. However, full text articles in electronic version, which offer larger sources of data, are currently available. Several questions arise as to whether the effort of scanning full text articles is worthy, or whether the information that can be extracted from the different sections of an article can be relevant. RESULTS: In this work we addressed those questions showing that the keyword content of the different sections of a standard scientific article (abstract, introduction, methods, results, and discussion) is very heterogeneous. CONCLUSIONS: Although the abstract contains the best ratio of keywords per total of words, other sections of the article may be a better source of biologically relevant data.
Keywords:Information Extraction, Full Text Article, Keyword, Gene Name, Data Mining, Text Mining
Source:BMC Bioinformatics
ISSN:1471-2105
Publisher:BioMed Central
Volume:4
Number:1
Page Range:20
Date:29 May 2003
Official Publication:https://doi.org/10.1186/1471-2105-4-20
PubMed:View item in PubMed

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