The strength of co-authorship in gene name disambiguation |
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Authors: | Richárd Farkas |
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Institution: | (1) Hungarian Academy of Science, Research Group on Artificial Intelligence, Aradi vertanuk tere, Szeged, Hungary |
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Abstract: | Background A biomedical entity mention in articles and other free texts is often ambiguous. For example, 13% of the gene names (aliases)
might refer to more than one gene. The task of Gene Symbol Disambiguation (GSD) – a special case of Word Sense Disambiguation
(WSD) – is to assign a unique gene identifier for all identified gene name aliases in biology-related articles. Supervised
and unsupervised machine learning WSD techniques have been applied in the biomedical field with promising results. We examine
here the utilisation potential of the fact – one of the special features of biological articles – that the authors of the
documents are known through graph-based semi-supervised methods for the GSD task. |
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Keywords: | |
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