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Situation Detection and Control using Spatio-temporal Analysis of Microblogs

机译:利用微博客的时空分析进行状态检测与控制

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Large volumes of spatio-temporal-thematic data being created using sites like Twitter and Jaiku, can potentially be combined to detect events, and understand various 'situations' as they are evolving at different spatio-temporal granularity across the world. Taking inspiration from traditional image pixels which represent aggregation of photon energies at a location, we consider aggregation of user interest levels at different geo-locations as social pixels. Combining such pixels spatio-temporally allows for creation of social images and video. Here, we describe how the use of relevant (media processing inspired) situation detection operators upon such 'images', and domain based rules can be used to decide relevant control actions. The ideas are showcased using a Swine flu monitoring application which uses Twitter data.
机译:使用Twitter和Jaiku等网站创建的大量时空主题数据,可以潜在地组合起来以检测事件,并了解各种“情况”,因为它们以世界各地不同的时空粒度发展。从代表一个位置光子能量聚集的传统图像像素中汲取灵感,我们将不同地理位置的用户兴趣水平聚集视为社交像素。时空组合这样的像素可以创建社交图像和视频。在这里,我们描述如何在此类“图像”上使用相关的(受媒体处理启发的)情况检测运算符,以及基于域的规则可用于决定相关的控制动作。使用使用Twitter数据的猪流感监测应用程序展示了这些想法。

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