Getting to the (c)ore of knowledge: mining biomedical literature.

Full Abstract

Literature mining is the process of extracting and combining facts from scientific publications. In recent years, many computer programs have been designed to extract various molecular biology findings from Medline abstracts or full-text articles. The present article describes the range of text mining techniques that have been applied to scientific documents. It divides 'automated reading' into four general subtasks:
text categorization, named entity tagging, fact extraction, and collection-wide analysis. Literature mining offers powerful methods to support knowledge discovery and the construction of topic maps and ontologies. An overview is given of recent developments in medical language processing. Special attention is given to the domain particularities of molecular biology, and the emerging synergy between literature mining and molecular databases accessible through Internet.

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Author information

Author/s: de Bruijn, Berry (B); Martin, Joel (J);

Affiliation: Institute for Information Technology, National Research Council, Montreal Road Bldg M50, Ottawa, Ont, Canada K1A 0R6. berry.debruijn@nrc.ca

Journal and publication information

Publication Type: Comparative Study; Journal Article

Journal: International journal of medical informatics (Int J Med Inform), published in Ireland. (Language: eng)

Reference: 2002-Dec; vol 67 (issue 1-3) : pp 7-18

Dates: Created 2002/12/03; Completed 2003/04/28; Revised 2007/11/15;

PMID: 12460628, status: MEDLINE (last retrieval date: 11/6/2008)

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Abstracting and Indexing as Topic
Artificial Intelligence
Databases as Topic
Humans
Internet

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