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Discover Computing
Erschienen in: Discover Computing 1-2/2016

01.04.2016 | Medical Information Retrieval

Biomedical term extraction: overview and a new methodology

verfasst von: Juan Antonio Lossio-Ventura, Clement Jonquet, Mathieu Roche, Maguelonne Teisseire

Erschienen in: Discover Computing | Ausgabe 1-2/2016

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Abstract

Terminology extraction is an essential task in domain knowledge acquisition, as well as for information retrieval. 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 all the 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.
Vorheriger Artikel Retrieval, visualization, and mining of large radiation dosage data
Nächster Artikel Evaluating multimodal relevance feedback techniques for medical image retrieval

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Fußnoten
13
by writing \(P(x)=\frac{nb(x)}{nb\_total}\), \(P(y)=\frac{nb(y)}{nb\_total}\), \(P(x,y)=\frac{nb(x,y)}{nb\_total}\).
 
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Metadaten
Titel
Biomedical term extraction: overview and a new methodology
verfasst von
Juan Antonio Lossio-Ventura
Clement Jonquet
Mathieu Roche
Maguelonne Teisseire
Publikationsdatum
01.04.2016
Verlag
Springer Netherlands
Erschienen in
Discover Computing / Ausgabe 1-2/2016
Print ISSN: 2948-2984
Elektronische ISSN: 2948-2992
DOI
https://doi.org/10.1007/s10791-015-9262-2

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