User-Qualified Group Search using Bidirectional Sweep Planes

Kyoung Ho Jung, Hong Jun Jang, Jaehwa Chung, Soon Young Jung

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

In this paper, we propose a nearest user-qualified group (NUG) query that searches a group of objects to obtain a result. In detail, given a dataset P, query q, distance δ, and cardinality k, the NUG query returns the nearest group of objects from q, such that more than k objects within δ distance from the point, called a representative, are in the group. Although the NUG query has large spectrum of applications, an efficient processing algorithm for NUG queries has not been studied so far. Therefore, we propose the plane sweep-based incremental search algorithm and heuristic that stops the plane sweep early to reduce the search space. A performance study is conducted on both synthetic and real datasets and our experimental results show that the proposed algorithm can improve the query performance in a variety of conditions.

Original languageEnglish
Pages (from-to)1-7
Number of pages7
JournalJournal of Ambient Intelligence and Humanized Computing
DOIs
Publication statusAccepted/In press - 2017 Nov 1

Fingerprint

Processing

Keywords

  • Nearest neighbor query
  • Nearest user-qualified group query
  • Spatial query processing

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

User-Qualified Group Search using Bidirectional Sweep Planes. / Jung, Kyoung Ho; Jang, Hong Jun; Chung, Jaehwa; Jung, Soon Young.

In: Journal of Ambient Intelligence and Humanized Computing, 01.11.2017, p. 1-7.

Research output: Contribution to journalArticle

@article{b6685312e53144de961147a7f69e342a,
title = "User-Qualified Group Search using Bidirectional Sweep Planes",
abstract = "In this paper, we propose a nearest user-qualified group (NUG) query that searches a group of objects to obtain a result. In detail, given a dataset P, query q, distance δ, and cardinality k, the NUG query returns the nearest group of objects from q, such that more than k objects within δ distance from the point, called a representative, are in the group. Although the NUG query has large spectrum of applications, an efficient processing algorithm for NUG queries has not been studied so far. Therefore, we propose the plane sweep-based incremental search algorithm and heuristic that stops the plane sweep early to reduce the search space. A performance study is conducted on both synthetic and real datasets and our experimental results show that the proposed algorithm can improve the query performance in a variety of conditions.",
keywords = "Nearest neighbor query, Nearest user-qualified group query, Spatial query processing",
author = "Jung, {Kyoung Ho} and Jang, {Hong Jun} and Jaehwa Chung and Jung, {Soon Young}",
year = "2017",
month = "11",
day = "1",
doi = "10.1007/s12652-017-0596-z",
language = "English",
pages = "1--7",
journal = "Journal of Ambient Intelligence and Humanized Computing",
issn = "1868-5137",
publisher = "Springer Verlag",

}

TY - JOUR

T1 - User-Qualified Group Search using Bidirectional Sweep Planes

AU - Jung, Kyoung Ho

AU - Jang, Hong Jun

AU - Chung, Jaehwa

AU - Jung, Soon Young

PY - 2017/11/1

Y1 - 2017/11/1

N2 - In this paper, we propose a nearest user-qualified group (NUG) query that searches a group of objects to obtain a result. In detail, given a dataset P, query q, distance δ, and cardinality k, the NUG query returns the nearest group of objects from q, such that more than k objects within δ distance from the point, called a representative, are in the group. Although the NUG query has large spectrum of applications, an efficient processing algorithm for NUG queries has not been studied so far. Therefore, we propose the plane sweep-based incremental search algorithm and heuristic that stops the plane sweep early to reduce the search space. A performance study is conducted on both synthetic and real datasets and our experimental results show that the proposed algorithm can improve the query performance in a variety of conditions.

AB - In this paper, we propose a nearest user-qualified group (NUG) query that searches a group of objects to obtain a result. In detail, given a dataset P, query q, distance δ, and cardinality k, the NUG query returns the nearest group of objects from q, such that more than k objects within δ distance from the point, called a representative, are in the group. Although the NUG query has large spectrum of applications, an efficient processing algorithm for NUG queries has not been studied so far. Therefore, we propose the plane sweep-based incremental search algorithm and heuristic that stops the plane sweep early to reduce the search space. A performance study is conducted on both synthetic and real datasets and our experimental results show that the proposed algorithm can improve the query performance in a variety of conditions.

KW - Nearest neighbor query

KW - Nearest user-qualified group query

KW - Spatial query processing

UR - http://www.scopus.com/inward/record.url?scp=85049568935&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85049568935&partnerID=8YFLogxK

U2 - 10.1007/s12652-017-0596-z

DO - 10.1007/s12652-017-0596-z

M3 - Article

AN - SCOPUS:85049568935

SP - 1

EP - 7

JO - Journal of Ambient Intelligence and Humanized Computing

JF - Journal of Ambient Intelligence and Humanized Computing

SN - 1868-5137

ER -