基于在线社交网络的流量事件检测

Alexandra S. Pereira, T. R. Silva, Fabrício A. Silva, A. Loureiro
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引用次数: 4

摘要

这项工作的重点是利用在线社交网络(OSNs)检测对大城市车辆交通有直接影响的事件,例如事故、道路建设翻新和交通堵塞。提出的模型旨在发现正在报告的问题,以及有关事件位置的信息。在对事件进行分类的任务中获得的结果是显著的,在确定通常交通事件的任务中达到高达94%的准确率和98%的一般命中率,此外在获得事件发生的城市点的参考方面也有希望的结果,召回率高达58%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Traffic Event Detection Using Online Social Networks
The focus of this work is on the detection of incidents that have a direct impact on the traffic of vehicles in large cities, such as, accidents, road constructions-renovations and traffic jams using Online Social Networks(OSNs). The proposed model aims to find problems being reported, as well as information on the location of the event. The results obtained were significant in the task of categorizing the incident, reaching up to 94% accuracy and 98% of general hits in the task of determining usual traffic incidents, besides promising results in obtaining references to the points in the city where the incidents take place, with up to 58% recall.
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