使用素数编码对轨迹长方体进行查询应答

E. Masciari
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引用次数: 2

摘要

轨迹数据流是由不同来源连续使用各种技术(例如,RFID标签,GPS, GSM网络)生成的与移动物体的时间和位置有关的大量数据。挖掘如此大量的数据是具有挑战性的,因为从这种特殊类型的数据中提取有用信息的可能性在许多应用场景中都是至关重要的,例如车辆交通管理、蜂窝网络切换、供应链管理。此外,空间数据流对其正确定义和获取都提出了有趣的挑战,从而使挖掘过程比传统的点数据更难。在本文中,我们解决了轨迹数据流在线分析处理的问题,当我们处理与元素顺序相关的数据(轨迹)时,这显示出真正的挑战。为了使查询步骤更加有效,我们提出了一个端到端框架。我们在真实世界的数据集上进行了几次测试,证实了所提出技术的效率和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Query answering on trajectory cuboids using prime numbers encodings
Trajectory data streams are huge amounts of data pertaining to time and position of moving objects generated by different sources continuously using a wide variety of technologies (e.g., RFID tags, GPS, GSM networks). Mining such amounts of data is challenging, since the possibility to extract useful information from this peculiar kind of data is crucial in many application scenarios such as vehicle traffic management, hand-off in cellular networks, supply chain management. Moreover, spatial data streams poses interesting challenges both for their proper definition and acquisition, thus making the mining process harder than for classical point data. In this paper, we address the problem of trajectory data streams On Line Analytical Processing, that revealed really challenging as we deal with data (trajectories) for which the order of elements is relevant. We propose an end to end framework in order to make the querying step quite effective. We performed several tests on real world datasets that confirmed the efficiency and effectiveness of the proposed techniques.
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