Data-to-Text Generation Improves Decision-Making Under Uncertainty
Journal Article
Gkatzia, D., Lemon, O., & Rieser, V. (2017)
Data-to-Text Generation Improves Decision-Making Under Uncertainty. IEEE Computational Intelligence Magazine, 12(3), 10-17. https://doi.org/10.1109/MCI.2017.2708998
Decision-making is often dependent on uncertain data, e.g. data associated with confidence scores or probabilities. This article presents a comparison of different information...
Natural Language Generation enhances human decision-making with uncertain information.
Conference Proceeding
Gkatzia, D., Lemon, O., & Rieser, V. (2016)
Natural Language Generation enhances human decision-making with uncertain information. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (264-268). https://doi.org/10.18653/v1/P16-2043
Decision-making is often dependent on uncertain data, e.g. data associated with confidence scores or probabilities. We present a comparison of different information presentati...
Generating Verbal Descriptions from Medical Sensor Data: A Corpus Study on User Preferences
Conference Proceeding
Gkatzia, D., Rieser, V., Mcsporran, A., Mcgowan, A., Mort, A., & Dewar, M. (2014)
Generating Verbal Descriptions from Medical Sensor Data: A Corpus Study on User Preferences. In BCS Health Informatics Scotland (HIS)
Understanding and interpreting medical sensor data is an essential part of pre-hospital care in medical emergencies, but requires training and previous knowledge. In this pape...
Multi-adaptive Natural Language Generation using Principal Component Regression
Conference Proceeding
Gkatzia, D., Hastie, H., & Lemon, O. (2014)
Multi-adaptive Natural Language Generation using Principal Component Regression. In Proceedings of the 8th International Natural Language Generation Conference, 138-142
We present FeedbackGen, a system that uses a multi-adaptive approach to Natural Language Generation. With the term 'multi-adaptive', we refer to a system that is able to adapt...