Abstract
The book gives an insight to Wordnet for Medical Events and applies commonsense computing and linguistic patterns to bridge the cognitive and affective gap between word-level medical data and the concept-level opinions conveyed by the medical contexts. This book introduces to a novel approach to decrease the gap between computational creativity and machine learning fields. This book also introduces to the microtext analysis which is an essential part for normalizing tweets and/or micro-blogs. This final section proposes a summary of contributions in terms of models, techniques and tools.
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Satapathy, R., Cambria, E., Hussain, A. (2017). Conclusion and Future Work. In: Sentiment Analysis in the Bio-Medical Domain. Socio-Affective Computing, vol 7. Springer, Cham. https://doi.org/10.1007/978-3-319-68468-0_5
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DOI: https://doi.org/10.1007/978-3-319-68468-0_5
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