Adapting Phrase-based Machine Translation to Normalise Medical Terms in Social Media Messages
Nut Limsopatham, Nigel Collier · 2015
Previous studies have shown that health reports in social media, such as Dai-lyStrength and Twitter, have potential for monitoring health conditions (e.g.adverse drug reactions, infectious diseases) in particular communities.However, in order for a machine to understand and make inferences on these health conditions, the ability to recognise when laymen's terms refer to a particular medical concept (i.e.text normalisation) is required.To achieve this, we propose to adapt an existing phrase-based machine translation (MT) technique and a vector representation of words to map between a social media phrase and a medical concept.We evaluate our proposed approach using a collection of phrases from tweets related to adverse drug reactions.Our experimental results show that the combination of a phrase-based MT technique and the similarity between word vector representations outperforms the baselines that apply only either of them by up to 55%.