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Querying Spatio-temporal Patterns in Mobile Phone-Call Databases

机译:查询移动电话数据库中的时空模式

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Call Detail Record (CDR) databases contain many millions of records with information about mobile phone calls, including the users' location when the call was made/received. This huge amount of spatio-temporal data opens the door for the study of human trajectories on a large scale without the bias that other sources, like GPS or WLAN networks, introduce in the population studied. Furthermore, it provides a platform for the development of a wide variety of studies ranging from the spread of diseases to planning of public transportation. Nevertheless, previous work on spatio-temporal queries does not provide a framework "flexible" enough for expressing the complexity of human trajectories. In this paper we present Spatio-Temporal Pattern System (STPS) to query spatio-temporal patterns in very large CDR databases. STPS uses a regular-expression query language that is intuitive and that allows for any combination of spatial and temporal predicates with constraints, including the use of variables. The design of the language takes into consideration the layout of the areas being covered by the cellular towers, as well as "areas" that label places of interested (e.g. neighborhoods, parks, etc). A full implementation of the STPS is currently running with real, very large CDR databases at Telefonica Research Labs. An extensive performance evaluation of the STPS shows that it can efficiently find very complex mobility patterns in large CDR databases.
机译:呼叫详细记录(CDR)数据库包含数百万条记录,其中包含有关移动电话的信息,包括拨打/接听电话时用户的位置。大量的时空数据为大规模研究人类轨迹打开了大门,而没有其他来源(如GPS或WLAN网络)引入研究人群的偏见。此外,它为疾病研究到公共交通规划等广泛研究的发展提供了平台。然而,先前关于时空查询的工作并未提供足够“灵活”的框架来表达人类轨迹的复杂性。在本文中,我们提出了时空模式系统(STPS)来查询非常大的CDR数据库中的时空模式。 STPS使用一种直观的正则表达式查询语言,并且可以将时空谓词与约束(包括变量的使用)进行任意组合。语言的设计考虑了蜂窝电话塔所覆盖区域的布局以及标记感兴趣的地方(例如,社区,公园等)的“区域”。目前,Telefonica Research Labs正在使用真实的,非常大的CDR数据库运行STPS的完整实现。对STPS的广泛性能评估表明,它可以在大型CDR数据库中有效地找到非常复杂的移动性模式。

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