Combining C-value and Keyword Extraction Methods for Biomedical Terms Extraction

Juan Antonio Lossio-Ventura 1, 2, * Clement Jonquet 2, 3 Mathieu Roche 4, 1 Maguelonne Teisseire 4, 1
* Corresponding author
1 ADVANSE - ADVanced Analytics for data SciencE
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
2 SMILE - Système Multi-agent, Interaction, Langage, Evolution
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : The objective of this work is to extract and to rank biomedical terms from free text. We present new extraction methods that use linguistic patterns specialized for the biomedical field, and use term extraction measures, such as C-value, and keyword extraction measures, such as Okapi BM25, and TFIDF. We propose several combinations of these measures to improve the extraction and ranking process. Our experiments show that an appropriate harmonic mean of C-value used with keyword extraction measures offers better precision results than used alone, either for the extraction of single-word and multi-words terms. We illustrate our results on the extraction of English and French biomedical terms from a corpus of laboratory tests. The results are validated by using UMLS (in English) and only MeSH (in French) as reference dictionary.
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Juan Antonio Lossio-Ventura, Clement Jonquet, Mathieu Roche, Maguelonne Teisseire. Combining C-value and Keyword Extraction Methods for Biomedical Terms Extraction. LBM: Languages in Biology and Medicine, Dec 2013, Tokyo, Japan. ⟨lirmm-01019991⟩

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