基于事件的Flickr和Panoramio地理标记图片集中人的活动和行为分析

S. Kisilevich, Milos Krstajic, D. Keim, N. Andrienko, G. Andrienko
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引用次数: 127

摘要

像Flickr和Panoramio这样的照片分享网站包含了来自世界各地的人们贡献的数百万张带有地理标签的图片。这些数据的特点给时空分析领域提出了新的挑战。在本文中,我们定义了几个不同的任务,这些任务与分析有吸引力的地方、兴趣点和比较不同用户群体在地理标记照片数据上的行为模式有关。我们对时间事件进行分析和比较,对一个城市的观光景点进行排名,并使用地理标记照片研究人们的流动性。我们采用系统的方法,通过应用可扩展的计算技术,使用统计和数据挖掘算法,结合交互式地理可视化来完成这些任务。我们提供探索性的可视化分析环境,允许分析人员检测空间和时间模式,并从大型地理标记照片集中提取额外的知识。我们通过将这些方法应用于世界上的几个地区来展示我们的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Event-Based Analysis of People's Activities and Behavior Using Flickr and Panoramio Geotagged Photo Collections
Photo-sharing websites such as Flickr and Panoramio contain millions of geotagged images contributed by people from all over the world. Characteristics of these data pose new challenges in the domain of spatio-temporal analysis. In this paper, we define several different tasks related to analysis of attractive places, points of interest and comparison of behavioral patterns of different user communities on geotagged photo data. We perform analysis and comparison of temporal events, rankings of sightseeing places in a city, and study mobility of people using geotagged photos. We take a systematic approach to accomplish these tasks by applying scalable computational techniques, using statistical and data mining algorithms, combined with interactive geo-visualization. We provide exploratory visual analysis environment, which allows the analyst to detect spatial and temporal patterns and extract additional knowledge from large geotagged photo collections. We demonstrate our approach by applying the methods to several regions in the world.
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