The flexible group spatial keyword query

Sabbir Ahmad, Rafi Kamal, Mohammed Eunus Ali*, Jianzhong Qi, Peter Scheuermann, Egemen Tanin

*Corresponding author for this work

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

4 Scopus citations

Abstract

We propose the flexible group spatial keyword query and algorithms to process three variants of the query in the spatial textual domain: (i) the group nearest neighbor with keywords query, which finds the data object that optimizes the aggregate cost function for the whole group Q of size n query objects, (ii) the subgroup nearest neighbor with keywords query, which finds the optimal subgroup of query objects and the data object that optimizes the aggregate cost function for a given subgroup size m (m ≤ n), and (iii) the multiple subgroup nearest neighbor with keywords query, which finds optimal subgroups and corresponding data objects for each of the subgroup sizes in the range [m, n]. We design query processing algorithms based on branch-and-bound and best-first paradigms. Finally, we conduct extensive experiments with two real datasets to show the efficiency of the proposed algorithms.

Original languageEnglish (US)
Title of host publicationDatabases Theory and Applications - 28th Australasian Database Conference, ADC 2017, Proceedings
EditorsXiaokui Xiao, Xin Cao, Zi Huang
PublisherSpringer Verlag
Pages3-16
Number of pages14
ISBN (Print)9783319681542
DOIs
StatePublished - 2017
Event28th Australasian Database Conference, ADC 2017 - Brisbane, Australia
Duration: Sep 25 2017Sep 28 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10538 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other28th Australasian Database Conference, ADC 2017
CountryAustralia
CityBrisbane
Period9/25/179/28/17

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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