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Collaborative Filtering of spatial-temporal information for crisis informatics

机译:危机信息学时空信息的协同筛选

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摘要

In a disaster, accurate information is a resource that is often in short supply. The combination of rapidly unfolding events and the frequent loss of communication infrastructure including mobile phones, landlines, Internet and television broadcast make it difficult to gain situational awareness. And while there is obvious value in aggregating information for centralized emergency authorities, disasters like Hurricane Katrina have shown that authoritative organizations are not always prepared to mobilize quickly enough. There is significant potential for systems that support self-organization and information sharing among the victims of a disaster. This paper discusses an application designed to share disaster information over an ad-hoc network built from common mobile devices (e.g. smart phones and PDAs). A Collaborative Filtering (CF) algorithm aggregates the observations of numerous distributed users and disseminates maps of disaster related events back to them. This paper describes a framework for analysis of disaster events, including both the availability of necessary resources (e.g. water and fuel) as well as disruptive events (e.g. downed power lines, leaks, etc). In addition, a spatial-temporal clustering algorithm combines the observations of multiple users into coherent reports. The goals of the framework are to quickly spread and accurately update vital information while resisting rumors and errors. The results demonstrate that sharing information in this way can increase the group's situational awareness.
机译:在灾难中,准确的信息是一种往往供不应求的资源。快速展开事件和频繁损失的通信基础设施频繁损失,包括移动电话,固定电话,互联网和电视广播,使得难以获得态势意识。虽然在集中式应急当局的汇总信息中存在明显的价值,但像飓风卡特里娜这样的灾害表明,权威机构并不总是准备好动员足够的动员。支持灾难受害者之间的自组织和信息共享的系统存在显着潜力。本文讨论了一个旨在通过由公共移动设备(例如智能手机和PDA)构建的Ad-hoc网络共享灾害信息的应用程序。协作过滤(CF)算法汇总了许多分布式用户的观察,并将灾难相关事件的映射传递给它们。本文介绍了分析灾难事件的框架,包括必要资源的可用性(例如水和燃料)以及破坏性事件(例如,下行电源线,泄漏等)。此外,空间 - 时间聚类算法将多个用户的观察结合到连贯的报告中。框架的目标是在抵制谣言和误差时快速传播和准确地更新重要信息。结果表明,以这种方式分享信息可以增加集团的情境感知。

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