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    Flexible Aggregate Nearest Neighbor Queries in Road Networks

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    Type
    Conference Paper
    Authors
    Yao, Bin
    Chen, Zhongpu
    Gao, Xiaofeng
    Shang, Shuo
    Ma, Shuai
    Guo, Minyi
    KAUST Department
    Computer Science Program
    Date
    2018-10-25
    Online Publication Date
    2018-10-25
    Print Publication Date
    2018-04
    Permanent link to this record
    http://hdl.handle.net/10754/630703
    
    Metadata
    Show full item record
    Abstract
    Aggregate nearest neighbor (ANN) query has been studied in both the Euclidean space and road networks. The flexible aggregate nearest neighbor (FANN) problem further generalizes ANN by introducing an extra flexibility. Given a set of data points P, a set of query points Q, and a user-defined flexibility parameter φ that ranges in (0, 1], an FA N N query returns the best candidate from P, which minimizes the aggregate (usually max or sum) distance to any φ |Q| objects in Q. In this paper, we focus on the problem in road networks (denoted as FANNR), and present a series of universal (i.e., suitable for both max and sum) algorithms to answer FANNR queries in road networks, including a Dijkstra-based algorithm enumerating P, a queue-based approach that processes data points from-near-To-far, and a framework that combines Incremental Euclidean Restriction (IER) and kNN. We also propose a specific exact solution to max-FANNR and a specific approximate solution to sum-FANNR which can return a near-optimal result with a guaranteed constant-factor approximation. These specific algorithms are easy to implement and can achieve excellent performance in some scenarios. Besides, we further extend the FANNR to k-FANNR, and successfully adapt most of the proposed algorithms to answer k-FANNR queries. We conduct a comprehensive experimental evaluation for the proposed algorithms on real road networks to demonstrate their superior efficiency and high quality.
    Citation
    Yao B, Chen Z, Gao X, Shang S, Ma S, et al. (2018) Flexible Aggregate Nearest Neighbor Queries in Road Networks. 2018 IEEE 34th International Conference on Data Engineering (ICDE). Available: http://dx.doi.org/10.1109/ICDE.2018.00074.
    Sponsors
    National Basic Research Program (973 Program, No.2015CB352403)
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    2018 IEEE 34th International Conference on Data Engineering (ICDE)
    Conference/Event name
    34th IEEE International Conference on Data Engineering, ICDE 2018
    DOI
    10.1109/ICDE.2018.00074
    Additional Links
    https://ieeexplore.ieee.org/document/8509295
    ae974a485f413a2113503eed53cd6c53
    10.1109/ICDE.2018.00074
    Scopus Count
    Collections
    Conference Papers; Computer Science Program

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