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dc.contributor.authorAlaqta, I
dc.contributor.authorWang, J
dc.contributor.authorAwrangjeb, M
dc.date.accessioned2020-03-02T06:36:13Z
dc.date.available2020-03-02T06:36:13Z
dc.date.issued2019
dc.identifier.isbn9783030352301
dc.identifier.issn0302-9743
dc.identifier.doi10.1007/978-3-030-35231-8_20
dc.identifier.urihttp://hdl.handle.net/10072/392029
dc.description.abstractCommunity search is defined as finding query-based communities within simple graphs. One of the most crucial community models is minimum degree subgraph in which each vertex has at least k neighbours. Due to the rapid development of location-based devices; however, simple graphs are unable to handle Location-Based Social Networks LBSN personal information such as interests and spatial locations. Hence, this paper aims to construct a Precomputed Hybrid Index Architecture (PHIA) for the sake of enhancing simple graphs to store and retrieve information of LBSN users. This method consists of two stages; the first is precomputing, and the second is index construction. Numerical testing showed that our hybrid index approach is reasonable because of its flexibility to combine different dimensions by adapting the wide used community model
dc.description.peerreviewedYes
dc.publisherSpringer
dc.relation.ispartofconferencename15th International Conference on Advanced Data Mining and Applications (ADMA 2019)
dc.relation.ispartofconferencetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.relation.ispartofdatefrom2019-11-21
dc.relation.ispartofdateto2019-11-23
dc.relation.ispartoflocationDalian, China
dc.relation.ispartofpagefrom277
dc.relation.ispartofpageto287
dc.relation.ispartofseriesAdvanced Data Mining and Applications
dc.relation.ispartofvolume11888
dc.subject.fieldofresearchArtificial Intelligence and Image Processing
dc.subject.fieldofresearchcode0801
dc.titlePrecomputing Hybrid Index Architecture for Flexible Community Search over Location-Based Social Networks
dc.typeConference output
dc.type.descriptionE1 - Conferences
dcterms.bibliographicCitationAlaqta, I; Wang, J; Awrangjeb, M, Precomputing Hybrid Index Architecture for Flexible Community Search over Location-Based Social Networks, Lecture Notes in Computer Science, 2019, 11888, pp. 277-287
dc.date.updated2020-02-28T05:56:38Z
dc.description.versionPost-print
gro.rights.copyright© Springer Nature Switzerland AG 2019. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher.The original publication is available at www.springerlink.com
gro.hasfulltextFull Text
gro.griffith.authorAwrangjeb, Mohammad
gro.griffith.authorAlaqta, Ismail


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