12 results

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...

How to Talk to Strangers: generating medical reports for first time users

Conference Proceeding
Gkatzia, D., Rieser, V., & Lemon, O. (2016)
How to Talk to Strangers: generating medical reports for first time users. In 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)https://doi.org/10.1109/FUZZ-IEEE.2016.7737739
We propose a novel approach for handling first-time users in the context of automatic report generation from timeseries data in the health domain. Handling first-time users is...

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...

From the Virtual to the RealWorld: Referring to Objects in Real-World Spatial Scenes

Conference Proceeding
Gkatzia, D., Rieser, V., Bartie, P., & Mackaness, W. (2015)
From the Virtual to the RealWorld: Referring to Objects in Real-World Spatial Scenes. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, 1936-1942. https://doi.org/10.18653/v1/d15-1224
Predicting the success of referring expressions (RE) is vital for real world applications such as navigation systems. Traditionally, research has focused on studying Referring...

Generating and Evaluating Landmark-Based Navigation Instructions in Virtual Environments

Conference Proceeding
Cercas Curry, A., Gkatzia, D., & Rieser, V. (2015)
Generating and Evaluating Landmark-Based Navigation Instructions in Virtual Environments. In Proceedings of the 15th European Workshop on Natural Language Generation, 90-94. https://doi.org/10.18653/v1/w15-4715
Referring to landmarks has been identified to lead to improved navigation instructions. However, a previous corpus study suggests that human “wizards” also choose to refer to ...

A Game-Based Setup for Data Collection and Task-Based Evaluation of Uncertain Information Presentation

Conference Proceeding
Gkatzia, D., Cercas Curry, A., Rieser, V., & Lemon, O. (2015)
A Game-Based Setup for Data Collection and Task-Based Evaluation of Uncertain Information Presentation. In Proceedings of the 15th European Workshop on Natural Language Generation, 112-113. https://doi.org/10.18653/v1/w15-4720
Decision-making is often dependent on uncertain data, e.g. data associated with confidence scores, such as probabilities. A concrete example of such data is weather data. We w...

A Snapshot of NLG Evaluation Practices 2005 - 2014

Conference Proceeding
Gkatzia, D., & Mahamood, S. (2015)
A Snapshot of NLG Evaluation Practices 2005 - 2014. https://doi.org/10.18653/v1/w15-4708
In this paper we present a snapshot of endto-end NLG system evaluations as presented in conference and journal papers1 over the last ten years in order to better understand th...

Exploratory Navigation for Runners Through Geographic Area Classification with Crowd-Sourced Data

Conference Proceeding
McGookin, D., Gkatzia, D., & Hastie, H. (2015)
Exploratory Navigation for Runners Through Geographic Area Classification with Crowd-Sourced Data. In Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services (357-361). https://doi.org/10.1145/2785830.2785879
Navigation when running is exploratory, characterised by both starting and ending in the same location, and iteratively foraging the environment to find areas with the most su...

Comparing Multi-label Classification with Reinforcement Learning for Summarisation of Time-series Data

Conference Proceeding
Gkatzia, D., Hastie, H., & Lemon, O. (2014)
Comparing Multi-label Classification with Reinforcement Learning for Summarisation of Time-series Data. In Proceedings of the Conference Volume 1: Long Papers. , (1231-1240). https://doi.org/10.3115/v1/p14-1116
We present a novel approach for automatic report generation from time-series data, in the context of student feedback generation. Our proposed methodology treats content selec...

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...