Smart City Development with Urban Transfer Learning
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The rapid development of big data techniques has offered great opportunities to develop smart city services in public safety, transportation management, city planning, etc. Meanwhile, the smart city development levels of different cities are still unbalanced. For a large of number of cities which just start development, the governments will face a critical cold-start problem, 'how to develop a new smart city service suffering from data scarcity?'. To address this problem, transfer learning is recently leveraged to accelerate the smart city development, which we term the urban transfer learning paradigm. This article investigates the common process of urban transfer learning, aiming to provide city governors and relevant practitioners with guidelines of applying this novel learning paradigm. Our guidelines include common transfer strategies to take, general steps to follow, and case studies to refer. We also summarize a few future research opportunities in urban transfer learning, and expect this article can attract more researchers into this promising area.
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