Mining Partners in Trajectories

Spatiotemporal data is everywhere, being gathered from different devices such as Earth Observation and GPS satellites, sensor networks and mobile gadgets. Spatiotemporal data collected from moving objects is of particular interest for a broad range of applications. In the last years, such applicatio...

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Bibliographic Details
Published inInternational journal of data warehousing and mining Vol. 16; no. 1; pp. 22 - 38
Main Authors Monteiro, Diego Vilela, Coelho dos Santos, Rafael Duarte, Ferreira, Karine Reis
Format Journal Article
LanguageEnglish
Published Hershey IGI Global 01.01.2020
Subjects
Algorithms
Clustering
Data mining
Object motion
Satellite observation
Sensors
Social networks
Spatiotemporal data
Time series
Trajectories
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Summary:Spatiotemporal data is everywhere, being gathered from different devices such as Earth Observation and GPS satellites, sensor networks and mobile gadgets. Spatiotemporal data collected from moving objects is of particular interest for a broad range of applications. In the last years, such applications have motivated many pieces of research on moving object trajectory data mining. In this article, it is proposed an efficient method to discover partners in moving object trajectories. Such a method identifies pairs of trajectories whose objects stay together during certain periods, based on distance time series analysis. It presents two case studies using the proposed algorithm. This article also describes an R package, called TrajDataMining, that contains algorithms for trajectory data preparation, such as filtering, compressing and clustering, as well as the proposed method Partner.
ISSN:1548-3924
1548-3932
DOI:10.4018/IJDWM.2020010102