All Outputs (5)

Bundle entropy as an optimized measure of consumers' systematic product choice combinations in mass transactional data (2022)
Conference Proceeding
Mansilla, R., Smith, G., Smith, A., & Goulding, J. (2022). Bundle entropy as an optimized measure of consumers' systematic product choice combinations in mass transactional data. In Proceedings 2022 IEEE International Conference on Big Data (1044-1053). https://doi.org/10.1109/BigData55660.2022.10021062

Understanding and measuring the predictability of consumer purchasing (basket) behaviour is of significant value. While predictability measures such as entropy have been well studied and leveraged in other sectors, their development and application t... Read More about Bundle entropy as an optimized measure of consumers' systematic product choice combinations in mass transactional data.

Towards Idea Mining: Problem-Solution Phrase Extraction fromText (2022)
Conference Proceeding
Liu, H., Brailsford, T., Goulding, J., Maul, T., Tan, T., & Chaudhuri, D. (2022). Towards Idea Mining: Problem-Solution Phrase Extraction fromText. In Advanced Data Mining and Applications 18th International Conference, ADMA 2022, Brisbane, QLD, Australia, November 28–30, 2022: Proceedings, Part II (3-14). https://doi.org/10.1007/978-3-031-22137-8_1

This paper investigates the feasibility of problem-solution phrases extraction from scientific publications using neural network approaches. Bidirectional Long Short-Term Memory with Conditional Random Fields (Bi-LSTM-CRFs) and Bidirectional Encoder... Read More about Towards Idea Mining: Problem-Solution Phrase Extraction fromText.

Public attitudes towards sharing loyalty card data for academic health research: a qualitative study (2022)
Journal Article
Dolan, E. H., Shiells, K., Goulding, J., & Skatova, A. (2022). Public attitudes towards sharing loyalty card data for academic health research: a qualitative study. BMC Medical Ethics, 23(1), Article 58. https://doi.org/10.1186/s12910-022-00795-8

Background: A growing number of studies show the potential of loyalty card data for use in health research. However , research into public perceptions of using this data is limited. This study aimed to investigate public attitudes towards donating lo... Read More about Public attitudes towards sharing loyalty card data for academic health research: a qualitative study.

Using mobile money data and call detail records to explore the risks of urban migration in Tanzania (2022)
Journal Article
Lavelle-Hill, R., Harvey, J., Smith, G., Mazumder, A., Ellis, M., Mwantimwa, K., & Goulding, J. (2022). Using mobile money data and call detail records to explore the risks of urban migration in Tanzania. EPJ Data Science, 11(8), Article 28. https://doi.org/10.1140/epjds/s13688-022-00340-y

Understanding what factors predict whether an urban migrant will end up in a deprived neighbourhood or not could help prevent the exploitation of vulnerable individuals. This study leveraged pseudonymized mobile money interactions combined with cell... Read More about Using mobile money data and call detail records to explore the risks of urban migration in Tanzania.

The Bayesian Spatial Bradley–Terry model: Urban deprivation modelling in Tanzania (2022)
Journal Article
Seymour, R. G., Sirl, D., Preston, S. P., Dryden, I. L., Ellis, M. J., Perrat, B., & Goulding, J. (2022). The Bayesian Spatial Bradley–Terry model: Urban deprivation modelling in Tanzania. Journal of the Royal Statistical Society: Series C, 71(2), 288-308. https://doi.org/10.1111/rssc.12532

Identifying the most deprived regions of any country or city is key if policy makers are to design successful interventions. However, locating areas with the greatest need is often surprisingly challenging in developing countries. Due to the logistic... Read More about The Bayesian Spatial Bradley–Terry model: Urban deprivation modelling in Tanzania.