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Spatio-temporal linkage over location-enhanced services
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Basik, Fuat, Gedik, Bugra, Etemoglu, Cagri and Ferhatosmanoglu, Hakan (2018) Spatio-temporal linkage over location-enhanced services. IEEE Transactions on Mobile Computing, 17 (2). pp. 447-460. doi:10.1109/TMC.2017.2711027 ISSN 1536-1233.
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Official URL: http://doi.org/10.1109/TMC.2017.2711027
Abstract
We are witnessing an enormous growth in the volume of data generated by various online services. An important portion of this data contains geographic references, since many of these services are location-enhanced and thus produce spatio-temporal records of their usage. We postulate that the spatio-temporal usage records belonging to the same real-world entity can be matched across records from different location-enhanced services. Linking spatio-temporal records enables data analysts and service providers to obtain information that they cannot derive by analyzing only one set of usage records. In this paper, we develop a new linkage model that can be used to match entities from two sets of spatio-temporal usage records belonging to two different location-enhanced services. This linkage model is based on the concept of k-l diversity — that we developed to capture both spatial and temporal aspects of the linkage. To realize this linkage model in practice, we develop a scalable linking algorithm called ST-Link, which makes use of effective spatial and temporal filtering mechanisms that significantly reduce the search space for matching users. Furthermore, ST-Link utilizes sequential scan procedures to avoid random disk access and thus scales to large datasets. We evaluated our work with respect to accuracy and performance using several datasets. Experiments show that ST-Link is effective in practice for performing spatio-temporal linkage and can scale to large datasets.
Item Type: | Journal Article | ||||||||
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Subjects: | Q Science > Q Science (General) T Technology > T Technology (General) |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||||
Library of Congress Subject Headings (LCSH): | Location-based services, Data mining, Statistical matching, Data integration (Computer science) | ||||||||
Journal or Publication Title: | IEEE Transactions on Mobile Computing | ||||||||
Publisher: | IEEE | ||||||||
ISSN: | 1536-1233 | ||||||||
Official Date: | February 2018 | ||||||||
Dates: |
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Volume: | 17 | ||||||||
Number: | 2 | ||||||||
Page Range: | pp. 447-460 | ||||||||
DOI: | 10.1109/TMC.2017.2711027 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||
Date of first compliant deposit: | 21 September 2017 | ||||||||
Date of first compliant Open Access: | 21 September 2017 |
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