Automatic assignment of biomedical categories: toward a generic approach

Motivation: We report on the development of a generic text categorization system designed to automatically assign biomedical categories to any input text. Unlike usual automatic text categorization systems, which rely on data-intensive models extracted from large sets of training data, our categoriz...

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Vydáno v:	Bioinformatics Ročník 22; číslo 6; s. 658 - 664
Hlavní autor:	Ruch, Patrick
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	England Oxford University Press 15.03.2006 Oxford Publishing Limited (England)
Témata:	Abstracting and Indexing as Topic - methods Algorithms Artificial Intelligence Documentation - methods MEDLINE Natural Language Processing Pattern Recognition, Automated - methods Periodicals as Topic Proteins - classification
ISSN:	1367-4803, 1460-2059, 1367-4811
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Shrnutí:	Motivation: We report on the development of a generic text categorization system designed to automatically assign biomedical categories to any input text. Unlike usual automatic text categorization systems, which rely on data-intensive models extracted from large sets of training data, our categorizer is largely data-independent. Methods: In order to evaluate the robustness of our approach we test the system on two different biomedical terminologies: the Medical Subject Headings (MeSH) and the Gene Ontology (GO). Our lightweight categorizer, based on two ranking modules, combines a pattern matcher and a vector space retrieval engine, and uses both stems and linguistically-motivated indexing units. Results and Conclusion: Results show the effectiveness of phrase indexing for both GO and MeSH categorization, but we observe the categorization power of the tool depends on the controlled vocabulary: precision at high ranks ranges from above 90% for MeSH to <20% for GO, establishing a new baseline for categorizers based on retrieval methods. Contact:Patrick.Ruch@sim.hcuge.ch
Bibliografie:	To whom correspondence should be addressed. istex:D55620CA35BE6A1C4A5346A269529F8130D77ADC ark:/67375/HXZ-BCXB2DZW-9 Associate Editor: Alfonso Valencia ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Article-2 ObjectType-Feature-1 content type line 23 ObjectType-Undefined-1 ObjectType-Feature-3
ISSN:	1367-4803 1460-2059 1367-4811
DOI:	10.1093/bioinformatics/bti783