| Machine learning innovations in address matching: A practical comparison of word2vec and CRFs S Comber, D Arribas‐Bel Transactions in GIS 23 (2), 334-348, 2019 | 59 | 2019 |
| A geographic data science framework for the functional and contextual analysis of human dynamics within global cities A Calafiore, G Palmer, S Comber, D Arribas-Bel, A Singleton Computers, Environment and Urban Systems 85, 101539, 2021 | 49 | 2021 |
| “Waiting on the train”: The anticipatory (causal) effects of Crossrail in Ealing S Comber, D Arribas-Bel Journal of Transport Geography 64, 13-22, 2017 | 21 | 2017 |
| Using convolutional autoencoders to extract visual features of leisure and retail environments S Comber, D Arribas-Bel, A Singleton, L Dolega Landscape and Urban Planning 202, 103887, 2020 | 16 | 2020 |
| Building hierarchies of retail centers using Bayesian multilevel models S Comber, D Arribas-Bel, A Singleton, G Dong, L Dolega Annals of the American Association of Geographers 110 (4), 1150-1173, 2020 | 12 | 2020 |
| Dynamic-IMD (D-IMD): Introducing activity spaces to deprivation measurement in London, Birmingham and Liverpool S Comber, S Park, D Arribas-Bel Cities 127, 103733, 2022 | 7 | 2022 |
| Demonstrating the utility of machine learning innovations in address matching to spatial socio-economic applications S Comber Region 7 (3), 17-37, 2020 | 5 | 2020 |
| An image library: The potential of imagery in (quantitative) social sciences D Arribas-Bel, F Rowe, M Chen, S Comber Handbook of Spatial Analysis in the Social Sciences, 528-543, 2022 | 3 | 2022 |
| Retail Research in the Age of Big Data: Guiding the Search for Answers S Comber PQDT-Global, 2021 | | 2021 |
| A Geographic Data Science Framework for the Functional and Contextual Analysis of Human Dynamics within Global Cities A Singleton, D Arribas-Bel, S Comber, A Calafiore, G Palmer | | |
Daniel Arribas-BelDepartment of Geography and PlanningVerified email at liverpool.ac.uk
