… gene symbols, English words and other biomedical terms is extensive … that word sense
disambiguation is critical for biomedical text mining and retrieval tasks because ambiguous words …

… A promising approach for achieving WSD is the use of machine learning techniques. … of the
problems noted for WSD in the biomedical domain was the relatively small number of training …

… domain, and within natural language processing (NLP), the word sense disambiguation (WSD)
problem … In this paper, we reported a machine learning approach for biomedical WSD. …

… Recent studies in the biomedical domain incorporate expert-… for disambiguation of biomedical
text data, a deep learning–… of concepts prevents the issue of sparsity (of word features) in …

… Word sense disambiguation is a core research field in … interest of artificial intelligence and
machine learning scientists and … to address the problem of word sense disambiguation. The …

… word sense disambiguation (WSD) problem across two biomedical domains—biomedical …
Our focus stays on supervised machine learning methods as applied on small data sets (up …

… machines applied to the supervised word sense disambiguation problem in the medical
domain. … information and machine learning algorithms on word sense disambiguation with small …

… In this paper, we present and evaluate a machine learning … disambiguation. Within the
natural language processing (NLP) domain, the word sense disambiguation (WSD) problem has …

… The current status of word sense disambiguation (WSD) … empirical, corpus-based machine
learning apthat have multiple full … Introduction to the special issue on word sense 29. Bruce R, …

… Since this is a problem for machine translation, information … an extensive study to disambiguate
biomedical abbreviations with … research and the need for it are not limited to the domains …