Cultural advice

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.

Aboriginal and Torres Strait Islander peoples are advised that ANU Library collections may include images, names, voices, and other representations of deceased persons.

Material in the collection may contain terms, language or views that reflect the period in which the item was created and may be considered inappropriate today.

MERLIN - A Tool for Multi-party Privacy-preserving Record Linkage

Simple item page
dc.contributor.authorRanbaduge, Thilina
dc.contributor.authorVatsalan, Dinusha
dc.contributor.authorChristen, Peter
dc.coverage.spatial2015 IEEE International Conference on Data Mining (ICDM)
dc.date.accessioned2016-06-14T23:21:18Z
dc.date.createdNovember 14-17, 2015
dc.date.issued2015
dc.date.updated2016-06-14T09:04:13Z
dc.description.abstractIn this paper, we present the current work and future directions on spatiotemporal frequent pattern mining algorithms for mining solar data. The current spatiotemporal pattern mining algorithms focus on spatiotemporal co-occurrence patterns. We reveal four types of spatiotemporal concepts that can be mined from solar data: event sequences, periodicity, spatiotemporal convergence and propagation. Throughout the paper, we exhibit examples of these concepts in the solar physics domain, and present related algorithms and the challenges of mining these concepts from solar data
dc.identifier.isbn9781467395038
dc.identifier.urihttp://hdl.handle.net/1885/103836
dc.publisherIEEE Computer Society
dc.relation.ispartofseries2015 IEEE International Conference on Data Mining
dc.sourceEfficient Entity Resolution with Adaptive and Interactive Training Data Selection
dc.titleMERLIN - A Tool for Multi-party Privacy-preserving Record Linkage
dc.typeConference paper
local.bibliographicCitation.lastpage1643
local.bibliographicCitation.startpage1640
local.contributor.affiliationRanbaduge, Thilina, College of Engineering and Computer Science, ANU
local.contributor.affiliationVatsalan, Dinusha, College of Engineering and Computer Science, ANU
local.contributor.affiliationChristen, Peter, College of Engineering and Computer Science, ANU
local.contributor.authoruidRanbaduge, Thilina, u5421298
local.contributor.authoruidVatsalan, Dinusha, u4908149
local.contributor.authoruidChristen, Peter, u4021539
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor080109 - Pattern Recognition and Data Mining
local.identifier.absseo970108 - Expanding Knowledge in the Information and Computing Sciences
local.identifier.ariespublicationu4334215xPUB1599
local.identifier.doi10.1109/ICDMW.2015.10
local.identifier.scopusID2-s2.0-84964720154
local.type.statusPublished Version

Downloads

Original bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
01_Ranbaduge_MERLIN_-_A_Tool_for_2015.pdf
Size:
533.53 KB
Format:
Adobe Portable Document Format
Download

Collections

ANU Research Publications

DSpace software copyright © 2002-2026 LYRASIS