Abstract
During an infectious disease outbreak, the contact tracing is regarded as the most crucial and effective way of disease control. As the users’ trajectories are widely obtainable due to the ubiquity of positioning devices, the contact tracing can be achieved by examining trajectories of confirmed patients to identify other trajectories that are contacted either directly or indirectly. In this paper, we propose a generalised Trajectory Contact Search (TCS) query, which models the contact tracing problem as well as other similar trajectory-based problems. In addition, we answer the query by proposing an iterative algorithm that finds contacted trajectories progressively along the transmission chains, and we further optimise each iteration in terms of time and space efficiency by proposing a hop scanning algorithm and a grid-based time interval tree. Extensive experiments on large-scale real-world data demonstrate the effectiveness of our proposed solutions over baseline algorithms.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Buchin, K., Buchin, M., van Kreveld, M., Speckmann, B., Staals, F.: Trajectory grouping structure. In: Dehne, F., Solis-Oba, R., Sack, J.-R. (eds.) WADS 2013. LNCS, vol. 8037, pp. 219–230. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-40104-6_19
Gudmundsson, J., van Kreveld, M., Speckmann, B.: Efficient detection of motion patterns in spatio-temporal data sets. In: Proceedings of the 12th Annual ACM International Workshop on Geographic Information Systems, pp. 250–257 (2004)
Jeung, H., Shen, H.T., Zhou, X.: Convoy queries in spatio-temporal databases. In: ICDE, pp. 1457–1459. IEEE (2008)
van Kreveld, M., Löffler, M., Staals, F., Wiratma, L.: A refined definition for groups of moving entities and its computation. Int. J. Comput. Geom. Appl 28(02), 181–196 (2018)
Li, Z., Ding, B., Han, J., Kays, R.: Swarm: mining relaxed temporal moving object clusters. PVLDB 3(1–2), 723–734 (2010)
Schmidt, J.M.: Interval stabbing problems in small integer ranges. In: Dong, Y., Du, D.-Z., Ibarra, O. (eds.) ISAAC 2009. LNCS, vol. 5878, pp. 163–172. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-10631-6_18
Tang, L.A., et al.: On discovery of traveling companions from streaming trajectories. In: ICDE, pp. 186–197. IEEE (2012)
Xu, J., Lu, H., Bao, Z.: IMO: a toolbox for simulating and querying “infected” moving objects. PVLDB 13(12), 2825–2828 (2020)
Zheng, K., Zheng, Y., Yuan, N.J., Shang, S., Zhou, X.: Online discovery of gathering patterns over trajectories. TKDE 26(8), 1974–1988 (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Chao, P., He, D., Li, L., Zhang, M., Zhou, X. (2021). Efficient Trajectory Contact Query Processing. In: Jensen, C.S., et al. Database Systems for Advanced Applications. DASFAA 2021. Lecture Notes in Computer Science(), vol 12681. Springer, Cham. https://doi.org/10.1007/978-3-030-73194-6_44
Download citation
DOI: https://doi.org/10.1007/978-3-030-73194-6_44
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-73193-9
Online ISBN: 978-3-030-73194-6
eBook Packages: Computer ScienceComputer Science (R0)