Word embeddings and recurrent neural networks based on Long-Short Term Memory nodes in supervised biomedical word sense disambiguation
Table 9: Macro and micro average LSTM results compared to SVM unigram and bigrams and word embeddings NLM WSD set.
['Configuration', 'Macro Accuracy', 'Micro Accuracy']
Using word embeddings significantly improve over using unigrams. LSTM shows some improvement in macro averaging. which is not significant compared to SVM and word embeddings.