Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/13346
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dc.contributor.authorDunstan, Neilen
local.source.editorEditor(s): Jiuyong Li, Longbing Cao, Can Wang, Kay Chen Tan, Bo Liu, Jian Pei, Vincent S Tsengen
dc.date.accessioned2013-08-29T17:26:00Z-
dc.date.issued2013-
dc.identifier.citationTrends and Applications in Knowledge Discovery and Data Mining. PAKDD 2013 International Workshops: DMApps, DANTH, QIMIE, BDM, CDA, CloudSD, Golden Coast, QLD, Australia, April 14-17, 2013, Revised Selected Papers, p. 26-35en
dc.identifier.isbn9783642403194en
dc.identifier.isbn9783642403187en
dc.identifier.urihttps://hdl.handle.net/1959.11/13346-
dc.description.abstractThe datacube is a conceptual data structure to support On-Line Analytical Processing (OLAP). It is essentially a series of tables organized according to attributes (called dimensions). Table rows (or cells) contain aggregated information for collections of records that satisfy value constraints for each dimension. The Statistics Tree (ST) uses a tree structure for storing the datacube in memory in order to optimize cell lookup time and handle a variety of types of cell-based queries. An Augmented ST (AST) is proposed with additional list structures within the ST. The additional lists link together the cells that comprise the tables of the datacube. An algorithm that builds table lists requires only a single traversal of the ST. Thus the AST supports both cell-level and table-level queries. Algorithms to build and update datacubes stored as ASTs are shown. A web-based wireless sensor network OLAP server based on the AST is described.en
dc.languageenen
dc.publisherSpringeren
dc.relation.ispartofTrends and Applications in Knowledge Discovery and Data Mining. PAKDD 2013 International Workshops: DMApps, DANTH, QIMIE, BDM, CDA, CloudSD, Golden Coast, QLD, Australia, April 14-17, 2013, Revised Selected Papersen
dc.relation.ispartofseriesLecture Notes in Computer Scienceen
dc.titleAn OLAP Server for Sensor Networks Using Augmented Statistics Treesen
dc.typeConference Publicationen
dc.relation.conferenceDMApps 2013: The International Workshop on Data Mining Applications in Industry and Governmenten
dc.identifier.doi10.1007/978-3-642-40319-4_3en
dc.subject.keywordsPattern Recognition and Data Miningen
local.contributor.firstnameNeilen
local.subject.for2008080109 Pattern Recognition and Data Miningen
local.subject.seo2008890301 Electronic Information Storage and Retrieval Servicesen
local.profile.schoolSchool of Science and Technologyen
local.profile.emailndunstan@une.edu.auen
local.output.categoryE1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.identifier.epublicationsrecordune-20130627-095823en
local.date.conference14th April, 2013en
local.conference.placeGold Coast, Australiaen
local.publisher.placeHeidelberg, Germanyen
local.format.startpage26en
local.format.endpage35en
local.identifier.scopusid84892869265en
local.series.issn1611-3349en
local.series.number7867en
local.peerreviewedYesen
local.contributor.lastnameDunstanen
dc.identifier.staffune-id:ndunstanen
local.profile.roleauthoren
local.identifier.unepublicationidune:13558en
dc.identifier.academiclevelAcademicen
local.title.maintitleAn OLAP Server for Sensor Networks Using Augmented Statistics Treesen
local.output.categorydescriptionE1 Refereed Scholarly Conference Publicationen
local.conference.detailsDMApps 2013: The International Workshop on Data Mining Applications in Industry and Government, Gold Coast, Australia, 14th April, 2013en
local.search.authorDunstan, Neilen
local.uneassociationUnknownen
local.year.published2013en
local.subject.for2020461199 Machine learning not elsewhere classifieden
local.subject.seo2020220302 Electronic information storage and retrieval servicesen
local.date.start2013-04-14-
Appears in Collections:Conference Publication
School of Science and Technology
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