Generating Unambiguous and Diverse Referring Expressions
Journal Article
Panagiaris, N., Hart, E., & Gkatzia, D. (2021)
Generating Unambiguous and Diverse Referring Expressions . Computer Speech and Language, 68, Article 101184. https://doi.org/10.1016/j.csl.2020.101184
Neural Referring Expression Generation (REG) models have shown promising results in generating expressions which uniquely describe visual objects. However, current REG models ...
Finding middle ground? Multi-objective Natural Language Generation from time-series data
Conference Proceeding
Gkatzia, D., Hastie, H., & Lemon, O. (2014)
Finding middle ground? Multi-objective Natural Language Generation from time-series data. In Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, volume 2: Short Papers. https://doi.org/10.3115/v1/e14-4041
A Natural Language Generation (NLG) system is able to generate text from nonlinguistic data, ideally personalising the content to a user’s specific needs. In some cases, howev...
The REAL Corpus: a crowd-sourced corpus of human generated and evaluated spatial references to real-world urban scenes
Conference Proceeding
Bartie, P., Mackaness, W., Gkatzia, D., & Rieser, V. (2016)
The REAL Corpus: a crowd-sourced corpus of human generated and evaluated spatial references to real-world urban scenes. In 10th International Conference on Language Resources and Evaluation (LREC)
We present a newly crowd-sourced data set of natural language references to objects anchored in complex urban scenes (In short: The REAL Corpus – Referring Expressions Anchore...
Opportunities and risks in the use of AI in career development practice
Journal Article
Wilson, M., Robertson, P., Cruickshank, P., & Gkatzia, D. (2022)
Opportunities and risks in the use of AI in career development practice. Journal of the National Institute for Career Education and Counselling, 48(1), 48-57. https://doi.org/10.20856/jnicec.4807
The Covid-19 pandemic required many aspects of life to move online. This accelerated a broader trend for increasing use of ICT and AI, with implications for both the world of ...
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...
Monitoring Users’ Behavior: Anti-Immigration Speech Detection on Twitter
Journal Article
Pitropakis, N., Kokot, K., Gkatzia, D., Ludwiniak, R., Mylonas, A., & Kandias, M. (2020)
Monitoring Users’ Behavior: Anti-Immigration Speech Detection on Twitter. Machine Learning and Knowledge Extraction, 2(3), 192-215. https://doi.org/10.3390/make2030011
The proliferation of social media platforms changed the way people interact online. However, engagement with social media comes with a price, the users’ privacy. Breaches of u...
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...
Commonsense-enhanced Natural Language Generation for Human-Robot Interaction
Conference Proceeding
Gkatzia, D. (in press)
Commonsense-enhanced Natural Language Generation for Human-Robot Interaction
Commonsense is vital for human communication, as it allows us to make inferences without explicitly mentioning the context. Equipping robots with commonsense knowledge would l...
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...
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...