With the rapid development of mobile platforms and smart devices, mobile applications have grown into one of the massive online markets. To build a high-quality and popular mobile application, well-designed user interfaces are important. This work proposes quantitative features to analyse mobile interface layouts to support data-driven design, including consistency, hierarchy, contrast, balance and harmony. A neural deep learning model is developed based on these features to predict user ratings of applications. These features and the model are evaluated on an open dataset, and the results prove that they can be utilised to reliably study and optimise mobile user interface design.
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