Show simple item record

dc.contributor.authorIslam, Md Saiful
dc.contributor.authorShen, Bojie
dc.contributor.authorWang, Can
dc.contributor.authorTaniar, David
dc.contributor.authorWang, Junhu
dc.date.accessioned2020-12-09T04:36:18Z
dc.date.available2020-12-09T04:36:18Z
dc.date.issued2020
dc.identifier.issn0306-4379
dc.identifier.doi10.1016/j.is.2020.101530
dc.identifier.urihttp://hdl.handle.net/10072/400084
dc.description.abstractThis paper presents a novel query for spatial databases, called reverse nearest neighborhood (RNH) query, to discover the neighborhoods that find a query facility as their nearest facility among other facilities in the dataset. Unlike a reverse nearest neighbor (RNN) query, an RNH query emphasizes on group of users instead of an individual user. More specifically, given a set of user locations U, a set of facility locations F, a query location q, a distance parameter ρ and a positive integer k, an RNH query returns all ρ-radius circles C enclosing at least k users u∈U, called neighborhoods (NH) such that the distance between q and C is less than the distance between C and any other facility f∈F. The RNH queries might have many practical applications including on demand facility placement and smart urban planning. We present an efficient approach for processing RNH queries on location data using R-tree based data indexing. In our approach, first we retrieve candidate RNH users by an efficient bound, prune and refine technique. Then, we incrementally discover RNHs of a query facility from these candidate RNH users. We also present the variants of RNH queries in spatial databases and propose solutions for them. We validate our approach by conducting extensive experiments with real datasets.
dc.description.peerreviewedYes
dc.description.sponsorshipGriffith University
dc.languageEnglish
dc.language.isoeng
dc.publisherElsevier
dc.relation.ispartofpagefrom101530
dc.relation.ispartofjournalInformation Systems
dc.relation.ispartofvolume92
dc.subject.fieldofresearchData management and data science not elsewhere classified
dc.subject.fieldofresearchSpatial data and applications
dc.subject.fieldofresearchQuery processing and optimisation
dc.subject.fieldofresearchcode460599
dc.subject.fieldofresearchcode460106
dc.subject.fieldofresearchcode460509
dc.subject.keywordsScience & Technology
dc.subject.keywordsComputer Science, Information Systems
dc.subject.keywordsReverse nearest neighborhood
dc.titleEfficient processing of reverse nearest neighborhood queries in spatial databases
dc.typeJournal article
dc.type.descriptionC1 - Articles
dcterms.bibliographicCitationIslam, MS; Shen, B; Wang, C; Taniar, D; Wang, J, Efficient processing of reverse nearest neighborhood queries in spatial databases, Information Systems, 2020, 92, pp. 101530
dcterms.licensehttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.date.updated2020-12-08T22:12:30Z
dc.description.versionVersion of Record (VoR)
gro.rights.copyright© 2020 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence (http://creativecommons.org/licenses/by-nc-nd/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
gro.hasfulltextFull Text
gro.griffith.authorIslam, Saiful
gro.griffith.authorWang, Can
gro.griffith.authorWang, John


Files in this item

This item appears in the following Collection(s)

  • Journal articles
    Contains articles published by Griffith authors in scholarly journals.

Show simple item record