Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/9441
Full metadata record
DC FieldValueLanguage
dc.contributor.authorCalders, Toon-
dc.contributor.authorRamon, Jan-
dc.contributor.authorVAN DYCK, Dries-
dc.date.accessioned2009-04-08T14:55:17Z-
dc.date.issued2008-
dc.identifier.citationGiannotti, F. (Ed.) ICDM 2008: EIGHTH IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS. p. 73-82.-
dc.identifier.isbn978-0-7695-3502-9-
dc.identifier.issn1550-4786-
dc.identifier.urihttp://hdl.handle.net/1942/9441-
dc.description.abstractIn graph mining, a frequency measure is anti-monotonic if the frequency of a pattern never exceeds the frequency of a subpattern. The efficiency and correctness of most graph pattern miners relies critically on this property. We study the case where the dataset is a single graph. Vanetik, Gudes and Shimony already gave sufficient and necessary conditions for anti-monotonicity of measures depending only on the edge-overlaps between the intances of the pattern in a labeled graph. We extend these results to homomorphisms, isomorphisms and homeomorphisms on both labeled and unlabeled, directed and undirected graphs, for vertex and edge overlap. We show a set of reductions between the different morphisms that preserve overlap.-
dc.format.extent265630 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoen-
dc.publisherIEEE COMPUTER SOC-
dc.relation.ispartofseriesIEEE International Conference on Data Mining-
dc.subject.othergraph support measure, overlap graph, anti-monotinicity-
dc.titleAnti-Monotonic Overlap-Graph Support Measures-
dc.typeProceedings Paper-
local.bibliographicCitation.authorsGiannotti, F.-
local.bibliographicCitation.conferencename8th IEEE International Conference on Data Mining-
local.bibliographicCitation.conferenceplacePisa, ITALY, dec 15-19, 2008-
dc.identifier.epage82-
dc.identifier.spage73-
local.bibliographicCitation.jcatC1-
local.type.refereedRefereed-
local.type.specifiedProceedings Paper-
dc.bibliographicCitation.oldjcatC1-
dc.identifier.doi10.1109/ICDM.2008.114-
dc.identifier.isi000264173600008-
dc.identifier.urlhttp://doi.ieeecomputersociety.org/10.1109/ICDM.2008.114-
local.bibliographicCitation.btitleICDM 2008: EIGHTH IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS-
item.fulltextWith Fulltext-
item.validationecoom 2010-
item.accessRightsOpen Access-
item.fullcitationCalders, Toon; Ramon, Jan & VAN DYCK, Dries (2008) Anti-Monotonic Overlap-Graph Support Measures. In: Giannotti, F. (Ed.) ICDM 2008: EIGHTH IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS. p. 73-82..-
Appears in Collections:Research publications
Files in This Item:
File Description SizeFormat 
icdm08.pdf259.4 kBAdobe PDFView/Open
Show simple item record

SCOPUSTM   
Citations

10
checked on Sep 4, 2020

WEB OF SCIENCETM
Citations

9
checked on Jun 21, 2022

Page view(s)

44
checked on Jun 24, 2022

Download(s)

174
checked on Jun 24, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.