在没有先验假设的情况下从稀疏CDR数据中提取规则移动性模式

IF 1.2 Q4 TELECOMMUNICATIONS
Oliver Burkhard, R. Ahas, Erki Saluveer, R. Weibel
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引用次数: 16

摘要

摘要在这项工作中,我们提出了两种方法,可以提取习惯性运动模式,并从用户的呼叫详细记录(CDR)中重建用户的基本运动,这种方法适用于只有中等数量CDR的用户,并且不会对用户的行为做出任何预先假设。这些方法允许在大规模研究中建立更全面的用户基础,因为还可以分析可能不得不丢弃的用户。第一种是基于关联挖掘的,计算强度不太高。第二个,我们命名为DAMOCLES,是基于从集群的日常活动中提取特殊的日常模式。这些方法是根据文献中常见的假设,例如周一至周五的工作周GPS地面实况,在平均200天内对140名用户的真实数据进行评估的。这两种方法显然都优于基准测试,并且对于许多用户来说,都检索到了类似的规律。此外,还进行了模拟研究,以便在更可控的环境中评估这些方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Extracting regular mobility patterns from sparse CDR data without a priori assumptions
Abstract In this work we present two methods that can extract habitual movement patterns and reconstruct the underlying movement of users from their call detail records (CDR) in a way that works for users with only moderate numbers of CDRs and that does not make any prior assumptions on the behaviour of the users. The methods allow for a more comprehensive user base in large-scale studies due to the fact that users that might otherwise have to be discarded can also be analysed. The first one is computationally not overly intense and is based on association mining. The second one, which we named DAMOCLES, is based on extracting idiosyncratic daily patterns from clustered daily activities. The methods are evaluated on real data of 140 users over an average of 200 days against benchmarks using assumptions commonly found in the literature such as a work week from Monday to Friday on GPS ground truth. Both methods clearly outperform the benchmarks and for many users retrieve similar regularities. Additionally a simulation study is performed that allows to evaluate the methods in a more controlled environment.
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来源期刊
CiteScore
3.70
自引率
8.70%
发文量
12
期刊介绍: The aim of this interdisciplinary and international journal is to provide a forum for the exchange of original ideas, techniques, designs and experiences in the rapidly growing field of location based services on networked mobile devices. It is intended to interest those who design, implement and deliver location based services in a wide range of contexts. Published research will span the field from location based computing and next-generation interfaces through telecom location architectures to business models and the social implications of this technology. The diversity of content echoes the extended nature of the chain of players required to make location based services a reality.
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