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SCENT: Scalable compressed monitoring of evolving multirelational social networks

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Lin, Yuru; Candan, Selcuk Selcuk; Sundaram, Hari; Xie, Lexing

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We propose SCENT, an innovative, scalable spectral analysis framework for internet scale monitoring of multirelational social media data, encoded in the form of tensor streams. In particular, a significant challenge is to detect key changes in the social

dc.contributor.authorLin, Yuru
dc.contributor.authorCandan, Selcuk Selcuk
dc.contributor.authorSundaram, Hari
dc.contributor.authorXie, Lexing
dc.date.accessioned2015-12-13T23:02:28Z
dc.identifier.issn1551-6857
dc.identifier.urihttp://hdl.handle.net/1885/84908
dc.description.abstractWe propose SCENT, an innovative, scalable spectral analysis framework for internet scale monitoring of multirelational social media data, encoded in the form of tensor streams. In particular, a significant challenge is to detect key changes in the social
dc.publisherAssociation for Computing Machinary, Inc.
dc.sourceACM Transactions on Multimedia Computing, Communications and Applications
dc.subjectKeywords: Multirelational learning; Social media; Social Network Analysis; Stream mining; Tensor analysis; Metadata; Signal detection; Social networking (online); Spectrum analysis; Tensors Multirelational learning; Social media; Social network analysis; Stream mining; Tensor analysis
dc.titleSCENT: Scalable compressed monitoring of evolving multirelational social networks
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume7 S
dc.date.issued2011
local.identifier.absfor080109 - Pattern Recognition and Data Mining
local.identifier.ariespublicationf5625xPUB13131
local.type.statusPublished Version
local.contributor.affiliationLin, Yuru, University of Pittsburgh
local.contributor.affiliationCandan, Selcuk Selcuk, Arizona State University
local.contributor.affiliationSundaram, Hari, Arizona State University
local.contributor.affiliationXie, Lexing, College of Engineering and Computer Science, ANU
local.description.embargo2037-12-31
local.bibliographicCitation.issue1
local.bibliographicCitation.startpage29/1
local.bibliographicCitation.lastpage22
local.identifier.doi10.1145/2037676.2037686
dc.date.updated2016-02-24T08:44:38Z
local.identifier.scopusID2-s2.0-84863634824
CollectionsANU Research Publications

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