BackgroundA 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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