Towards nearest collection search on spatial databases

Hong Jun Jang, Woo Sung Choi, Kyeong Seok Hyun, Kyoung Ho Jung, Soon Young Jung, Young Sik Jeong, Jaehwa Chung

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In this paper, for the first time, we present the concept of nearest collection (NC) search. Given a set of spatial data points D and a query point q, a nearest collection search retrieves a certain subset c (|c| = k), called collection from D. We formally define a collection as clustered k objects and the nearest collection search problem. Since the brute-force approach of this problem requires large computational cost, we propose two approaches using database techniques to reduce search space. The first approach is the multiple query method which uses existing method (i.e. k-nearest neighbor query) based on normal R-tree. The second approach is the effective NC query processing based on the branch and bound method using an aggregate R-tree (simply aR-tree). Our experimental results show that the efficiency and effectiveness of our proposed approach.

Original languageEnglish
Title of host publicationLecture Notes in Electrical Engineering
PublisherSpringer Verlag
Number of pages8
Volume280 LNEE
ISBN (Print)9783642416705
Publication statusPublished - 2014
Event8th International Conference on Ubiquitous Information Technologies and Applications, CUTE 2013 - Danang, Viet Nam
Duration: 2013 Dec 182013 Dec 20

Publication series

NameLecture Notes in Electrical Engineering
Volume280 LNEE
ISSN (Print)18761100
ISSN (Electronic)18761119


Other8th International Conference on Ubiquitous Information Technologies and Applications, CUTE 2013
Country/TerritoryViet Nam


  • K-nearest neighbor query
  • Nearest collection query
  • Spatial database

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering


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