dc.creatorANDRÉS GAGO ALONSO
dc.creatorAbel Puentes Luberta
dc.creatorJESUS ARIEL CARRASCO OCHOA
dc.creatorJOSE FRANCISCO MARTINEZ TRINIDAD
dc.date2010
dc.date.accessioned2023-07-25T16:23:34Z
dc.date.available2023-07-25T16:23:34Z
dc.identifierhttp://inaoe.repositorioinstitucional.mx/jspui/handle/1009/1395
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7806590
dc.descriptionMost of the Frequent Connected Subgraph Mining (FCSM) algorithms have been focused on detecting duplicate candidates using canonical form (CF) tests. CF tests have high computational complexity, which affects the efficiency of graph miners. In this paper, we introduce novel properties of the canonical adjacency matrices for reducing the number of CF tests in FCSM. Based on these properties, a new algorithm for frequent connected subgraph mining called grCAM is proposed. The experiments on real world datasets show the impact of the proposed properties in FCSM. Besides, the performance of our algorithm is compared against some other reported algorithms.
dc.formatapplication/pdf
dc.languageeng
dc.publisherIOS Press
dc.relationcitation:Gago-Alonso, A., et al., (2010). A new algorithm for mining frequent connected subgraphs based on adjacency matrices, Intelligent Data Analysis, (May): 1-26
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0
dc.subjectinfo:eu-repo/classification/Data mining/Data mining
dc.subjectinfo:eu-repo/classification/Graph mining/Graph mining
dc.subjectinfo:eu-repo/classification/Frequent subgraphs/Frequent subgraphs
dc.subjectinfo:eu-repo/classification/Labeled graphs/Labeled graphs
dc.subjectinfo:eu-repo/classification/Canonical adjacency matrices/Canonical adjacency matrices
dc.subjectinfo:eu-repo/classification/cti/1
dc.subjectinfo:eu-repo/classification/cti/12
dc.subjectinfo:eu-repo/classification/cti/1203
dc.subjectinfo:eu-repo/classification/cti/1203
dc.titleA new algorithm for mining frequent connected subgraphs based on adjacency matrices
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/acceptedVersion
dc.audiencestudents
dc.audienceresearchers
dc.audiencegeneralPublic


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