Outputs (37)

A Game-Based Setup for Data Collection and Task-Based Evaluation of Uncertain Information Presentation (2015)
Presentation / Conference Contribution
Gkatzia, D., Cercas Curry, A., Rieser, V., & Lemon, O. (2015, September). A Game-Based Setup for Data Collection and Task-Based Evaluation of Uncertain Information Presentation. Presented at 15th European Workshop on Natural Language Generation (ENLG 2015), University of Brighton, Brighton, UK

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 will demo a game-based setup for exploring the effectiveness of different ap... Read More about A Game-Based Setup for Data Collection and Task-Based Evaluation of Uncertain Information Presentation.

Exploratory Navigation for Runners Through Geographic Area Classification with Crowd-Sourced Data (2015)
Presentation / Conference Contribution
McGookin, D., Gkatzia, D., & Hastie, H. (2015, August). Exploratory Navigation for Runners Through Geographic Area Classification with Crowd-Sourced Data. Presented at 17th International Conference on Human-Computer Interaction with Mobile Devices and Services, Copenhagen, Denmark

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 suitable running conditions. Runners do not wish to be explicitly directed, o... Read More about Exploratory Navigation for Runners Through Geographic Area Classification with Crowd-Sourced Data.

Finding middle ground? Multi-objective Natural Language Generation from time-series data (2014)
Presentation / Conference Contribution
Gkatzia, D., Hastie, H., & Lemon, O. (2014, April). Finding middle ground? Multi-objective Natural Language Generation from time-series data. Presented at Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, volume 2: Short Papers, Gothenburg, Sweden

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, however, there are multiple stakeholders with their own individual goals, needs... Read More about Finding middle ground? Multi-objective Natural Language Generation from time-series data.

Comparing Multi-label Classification with Reinforcement Learning for Summarisation of Time-series Data (2014)
Presentation / Conference Contribution
Gkatzia, D., Hastie, H., & Lemon, O. (2014, June). Comparing Multi-label Classification with Reinforcement Learning for Summarisation of Time-series Data. Presented at The 52nd Annual Meeting of the Association for Computational Linguistics, Baltimore

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 selection as a multi-label (ML)
classification problem, which takes as input ti... Read More about Comparing Multi-label Classification with Reinforcement Learning for Summarisation of Time-series Data.

Generating Verbal Descriptions from Medical Sensor Data: A Corpus Study on User Preferences (2014)
Presentation / Conference Contribution
Gkatzia, D., Rieser, V., Mcsporran, A., Mcgowan, A., Mort, A., & Dewar, M. (2014, September). Generating Verbal Descriptions from Medical Sensor Data: A Corpus Study on User Preferences. Presented at BCS Health Informatics Scotland, Glasgow

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 paper, we describe ongoing work towards a medical decision support tool, which... Read More about Generating Verbal Descriptions from Medical Sensor Data: A Corpus Study on User Preferences.

Multi-adaptive Natural Language Generation using Principal Component Regression (2014)
Presentation / Conference Contribution
Gkatzia, D., Hastie, H., & Lemon, O. (2014, June). Multi-adaptive Natural Language Generation using Principal Component Regression. Presented at International Natural Language Generation Conference (INLG)

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 its content to different user groups simultaneously, in our case adapting... Read More about Multi-adaptive Natural Language Generation using Principal Component Regression.

Generating student feedback from time-series data using Reinforcement Learning (2013)
Presentation / Conference Contribution
Gkatzia, D., Hastie, H., Janarthanam, S., & Lemon, O. (2013, August). Generating student feedback from time-series data using Reinforcement Learning. Presented at 14th European Workshop On Natural Language Generation, Sofia, Bulgaria

We describe a statistical Natural LanguageGeneration (NLG) method for summarisa-tion of time-series data in the context offeedback generation for students. In thispaper, we initially present a method forcollecting time-series data f... Read More about Generating student feedback from time-series data using Reinforcement Learning.