论文标题
索引城市：用地理标记的数据表达城市偏好的个人模型
Indexical Cities: Articulating Personal Models of Urban Preference with Geotagged Data
论文作者
论文摘要
如何在去过那里之前评估喜欢城市或社区的潜力。到目前为止，城市质量的概念与全球城市排名有关，在该城市排名中，在给定参数的网格或经验和社会学方法的网格中，对城市进行了评估，通常受到可用信息的数量的限制。这项研究使用了最先进的机器学习技术和数千种来自各种城市文化的地理标签卫星和透视图像，这是在城市空间中的个人喜好的特征，并预测了特定观察者的一系列未知的可爱场所。与大多数城市感知研究不同，我们的意图不是提供客观地衡量城市质量的方式，而是要描绘城市或索引城市的个人观点。
How to assess the potential of liking a city or a neighborhood before ever having been there. The concept of urban quality has until now pertained to global city ranking, where cities are evaluated under a grid of given parameters, or either to empirical and sociological approaches, often constrained by the amount of available information. Using state of the art machine learning techniques and thousands of geotagged satellite and perspective images from diverse urban cultures, this research characterizes personal preference in urban spaces and predicts a spectrum of unknown likeable places for a specific observer. Unlike most urban perception studies, our intention is not by any means to provide an objective measure of urban quality, but rather to portray personal views of the city or Cities of Indexes.
