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dc.contributor.authorCuzzocrea, Alfredo
dc.contributor.authorJiang, Fan
dc.contributor.authorLeung, Carson K.
dc.date.accessioned2016-03-08T22:14:41Z
dc.date.available2016-03-08T22:14:41Z
dc.date.issued2015
dc.identifier.citationA. Cuzzocrea, F. Jiang, & C.K. Leung. Frequent subgraph mining from streams of linked graph structured data. In Proc. EDBT/ICDT Workshops 2015, pp. 237-244.en_US
dc.identifier.otherhttp://ceur-ws.org/Vol-1330/paper-37.pdf
dc.identifier.urihttp://hdl.handle.net/1993/31152
dc.descriptionA. Cuzzocrea, F. Jiang, & C.K. Leung. Frequent subgraph mining from streams of linked graph structured data. In Proc. EDBT/ICDT Workshops 2015, pp. 237-244. This paper is published in the Workshop Proceedings of the EDBT/ICDT 2015 Joint Conference (March 27, 2015, Brussels, Belgium) on CEUR-WS.org (ISSN 1613-0073) under the terms of the Creative Commons license CC-by-nc-nd 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0).en_US
dc.description.abstractNowadays, high volumes of high-value data (e.g., semantic web data) can be generated and published at a high velocity. A collection of these data can be viewed as a big, interlinked, dynamic graph structure of linked resources. Embedded in them are implicit, previously unknown, and potentially useful knowledge. Hence, efficient knowledge discovery algorithms for mining frequent subgraphs from these dynamic, streaming graph structured data are in demand. Some existing algorithms require very large memory space to discover frequent subgraphs; some others discover collections of frequently co-occurring edges (which may be disjoint). In contrast, we propose---in this paper---algorithms that use limited memory space for discovering collections of frequently co-occurring connected edges. Evaluation results show the effectiveness of our algorithms in frequent subgraph mining from streams of linked graph structured data.en_US
dc.description.sponsorshipNatural Sciences and Engineering Research Council of Canada (NSERC); University of Manitobaen_US
dc.language.isoengen_US
dc.publisherCEUR Workshop Proceedingsen_US
dc.relation.ispartofseriesCEUR Workshop Proceedings (ISSN 1613-0073);Vol. 1330
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectdata miningen_US
dc.subjectfrequent patternsen_US
dc.subjectgraph structured dataen_US
dc.subjectlinked dataen_US
dc.subjectextending database technologyen_US
dc.subjectdatabase theoryen_US
dc.titleFrequent subgraph mining from streams of linked graph structured dataen_US
dc.typeArticleen_US
dc.typeinfo:eu-repo/semantics/article


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