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A Dynamic Data Structure for Approximate Proximity Queries in Trajectory Data

Published:07 November 2017Publication History

ABSTRACT

Let S be a set of n polygonal trajectories in the plane and k be a fixed constant. We present a data structure to store S so that, given a k-vertex query trajectory Q, we can answer the following queries approximately:

• Nearest neighbor query: given a query trajectory Q, report the trajectory in S with minimum Fréchet distance to Q.

• Top-j query: given a query trajectory Q and a positive integer j, report the j trajectories in S with minimum Fréchet distance to Q.

• Range reporting query: given a query trajectory Q and a number δmax, report all trajectories in S with Fréchet distance at most δmax to Q.

• Similarity query: given a query trajectory Q and a trajectory τ ∈ S, report the Fréchet distance between Q and τ.

Our data structure answers these queries approximately with an additive error that is at most ϵ · reach(Q) for a given fixed constant ϵ > 0, where reach(Q) is the maximum distance between the start vertex of Q and any other vertex of Q. Furthermore, our query procedures ignore trajectories whose Fréchet distance to the query Q is very large. That is, if no trajectory is close to the query trajectory then no answer might be returned. The data structure uses O(n/ϵ2k) space and answers each of the queries above in time O(1 + #answers). Our data structure is the first one that can answer all these queries with provable error guarantees. Moreover, it is fully dynamic: inserting and deleting a trajectory with m vertices takes O(1/ϵ2k (m + log(1/ϵ))) and O(1/ϵ2k) amortized time, respectively. Finally, we empirically evaluate our data structure.

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      • Published in

        cover image ACM Conferences
        SIGSPATIAL '17: Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
        November 2017
        677 pages
        ISBN:9781450354905
        DOI:10.1145/3139958

        Copyright © 2017 Owner/Author

        Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 7 November 2017

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        • Refereed limited

        Acceptance Rates

        SIGSPATIAL '17 Paper Acceptance Rate39of193submissions,20%Overall Acceptance Rate220of1,116submissions,20%

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