Adaptive City Characteristics: How Location Familiarity Changes What Is Regionally Descriptive

Vikas Kumar, Saeideh Bakhshi, L. Kennedy, David A. Shamma
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引用次数: 1

Abstract

Proliferation of GPS-enabled mobile devices has brought a plurality of location-aware applications leveraging the location characteristics in the shared content, like photos and check-ins. While these applications provide contextual and relevant information, they also assume geo-tagged contents to be representative of the geo-bounded characteristics of location. In this paper, however, we show that the characteristics geo-tagged contents capture about a location can vary based on the familiarity of user (sharing the content) with the location. Using a large dataset of geo-tagged photos, we learn descriptive spatial photo characteristics and user temporal-location-familiarity to highlight unique characteristics photos capture of location, which vary significantly if taken by locals versus tourists. We then propose a ranking-approach to find most representative photos for a given city. A user-based evaluation shows photos are more diverse and characteristic of location compared to other popular baselines while being representative of how locals and tourists would describe the city.
适应性城市特征:地点熟悉度如何改变区域描述
支持gps功能的移动设备的激增带来了许多利用共享内容(如照片和签到)中的位置特征的位置感知应用程序。虽然这些应用程序提供上下文和相关信息,但它们也假设地理标记的内容代表地理位置的边界特征。然而,在本文中,我们展示了地理标记内容捕获的关于位置的特征可以根据用户对位置的熟悉程度(共享内容)而变化。使用地理标记照片的大型数据集,我们学习描述性空间照片特征和用户时间位置熟悉度,以突出位置照片捕获的独特特征,这些特征在当地人和游客拍摄时差异很大。然后,我们提出了一种排名方法来查找给定城市的最具代表性的照片。一项基于用户的评估显示,与其他流行的基准相比,照片更具多样性和位置特征,同时也代表了当地人和游客对这座城市的描述。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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