Publication Type
Journal Article
Version
acceptedVersion
Publication Date
7-2015
Abstract
Aggregate nearest neighbor query, which returns an optimal target 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 two algorithms to process MANN query on road networks when aggregate function is max. Then, we extend the algorithms to support other aggregate functions (e.g., sum). Extensive experiments are conducted to examine the behaviors of the solutions in terms of five parameters affecting the performance. The overall experiments show that our strategies to minimize the response time are effective.
Keywords
Query processing, Aggregate nearest neighbor, Road networks, Spatial databases
Discipline
Databases and Information Systems | Transportation
Research Areas
Data Science and Engineering
Publication
Information Sciences
Volume
310
First Page
52
Last Page
68
ISSN
0020-0255
Identifier
10.1016/j.ins.2015.03.028
Publisher
Elsevier
Citation
SUN, Weiwei; CHEN, Chong; ZHENG, Baihua; CHEN, Chunan; ZHU, Liang; LIU, Weimo; and HUANG, Yan.
Fast Optimal Aggregate Point Search for a Merged Set on Road Networks. (2015). Information Sciences. 310, 52-68.
Available at: https://ink.library.smu.edu.sg/sis_research/2867
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1016/j.ins.2015.03.028