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dc.contributor.authorHebden, P
dc.contributor.authorPearce, AR
dc.date.available2014-05-22T04:47:34Z
dc.date.issued2005-01-01
dc.identifierhttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000235261200029&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=d4d813f4571fa7d6246bdc0dfeca3a1c
dc.identifier.citationHebden, P. & Pearce, A. R. (2005). Bloom filters for data aggregation and discovery: a hierarchical clustering approach. PROCEEDINGS OF THE 2005 INTELLIGENT SENSORS, SENSOR NETWORKS & INFORMATION PROCESSING CONFERENCE, 2005, pp.175-180. IEEE. https://doi.org/10.1109/issnip.2005.1595575.
dc.identifier.isbn0-7803-9399-6
dc.identifier.isbn9780780393998
dc.identifier.urihttp://hdl.handle.net/11343/31978
dc.descriptionInternational Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)
dc.languageEnglish
dc.publisherIEEE
dc.sourceIntelligent Sensors, Sensor Networks and Information Processing Conference
dc.subjectArtificial Intelligence and Image Processing
dc.titleBloom filters for data aggregation and discovery: a hierarchical clustering approach
dc.typeConference Paper
dc.identifier.doi10.1109/issnip.2005.1595575
melbourne.peerreviewPeer Reviewed
melbourne.affiliationThe University of Melbourne
melbourne.affiliation.departmentComputer Science and Software Engineering
melbourne.source.titlePROCEEDINGS OF THE 2005 INTELLIGENT SENSORS, SENSOR NETWORKS & INFORMATION PROCESSING CONFERENCE
melbourne.source.volume2005
melbourne.source.pages175-180
dc.research.codefor0801
melbourne.publicationid42797
melbourne.elementsid272822
melbourne.contributor.authorPearce, Adrian
melbourne.contributor.authorHEBDEN, PETER
melbourne.event.locationMelbourne, AUSTRALIA
melbourne.accessrightsThis item is currently not available from this repository


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