Efficient Trajectory Contact Query Processing

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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.

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Chao, P., He, D., Li, L., Zhang, M., & Zhou, X. (2021). Efficient Trajectory Contact Query Processing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12681 LNCS, pp. 658–666). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-73194-6_44

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