Biomedical term extraction: overview and a new methodology - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Access content directly
Journal Articles Information Retrieval Journal Year : 2016

Biomedical term extraction: overview and a new methodology

Abstract

Terminology extraction is an essential task in domain knowledge acquisition, as well as for Information Retrieval (IR). It is also a mandatory first step aimed at building/enriching terminologies and ontologies. As often proposed in the literature, existing terminology extraction methods feature linguistic and statistical aspects and solve some problems related (but not completely) to term extraction, e.g. noise, silence, low frequency, large-corpora, complexity of the multi-word term extraction process. In contrast, we propose a cutting edge methodology to extract and to rank biomedical terms, covering the all mentioned problems. This methodology offers several measures based on linguistic, statistical, graphic and web aspects. These measures extract and rank candidate terms with excellent precision: we demonstrate that they outperform previously reported precision results for automatic term extraction, and work with different languages (English, French, and Spanish). We also demonstrate how the use of graphs and the web to assess the significance of a term candidate, enables us to outperform precision results. We evaluated our methodology on the biomedical GENIA and LabTestsOnline corpora and compared it with previously reported measures.
Fichier principal
Vignette du fichier
manley.pdf (1.51 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

lirmm-01274539 , version 1 (16-02-2016)

Identifiers

Cite

Juan Antonio Lossio-Ventura, Clement Jonquet, Mathieu Roche, Maguelonne Teisseire. Biomedical term extraction: overview and a new methodology. Information Retrieval Journal, 2016, Medical Information Retrieval, 19 (1), pp.59-99. ⟨10.1007/s10791-015-9262-2⟩. ⟨lirmm-01274539⟩
589 View
958 Download

Altmetric

Share

Gmail Facebook X LinkedIn More