Conference Proceeding Article
Aggregate nearest neighbor query, which returns a common interesting point that minimizes the aggregate distance for a given query point set, is one of the most important operations in spatial databases and their application domains. This paper addresses the problem of finding the aggregate nearest neighbor for a merged set that consists of the given query point set and multiple points needed to be selected from a candidate set, which we name as merged aggregate nearest neighbor(MANN) query. This paper proposes an effective algorithm to process MANN query in road networks based on our pruning strategies. Extensive experiments are conducted to examine the behaviors of the solutions and the overall experiments show that our strategies to minimize the response time are effective and achieve several orders of magnitude speedup compared with the baseline methods.
Query Processing, Nearest Neighbor, Road Networks
Databases and Information Systems | Numerical Analysis and Scientific Computing | Transportation
Data Management and Analytics
CIKM '13: Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, 27 October - 1 November 2013, San Francisco
City or Country
SUN, Weiwei; CHEN, Chong; ZHENG, Baihua; CHEN, Chunan; and ZHU, Liang.
Merged Aggregate Nearest Neighbor Query Processing in Road Networks. (2013). CIKM '13: Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, 27 October - 1 November 2013, San Francisco. 2243-2248. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/1954
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