Effectively and efficiently mining frequent patterns from dense graph streams on disk

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dc.contributor.authorBraun, Peter
dc.contributor.authorCameron, Juan J.
dc.contributor.authorCuzzocrea, Alfredo
dc.contributor.authorJiang, Fan
dc.contributor.authorLeung, Carson K.
dc.date.accessioned2017-02-13T15:34:30Z
dc.date.available2017-02-13T15:34:30Z
dc.date.issued2014
dc.descriptionP. Braun, J.J. Cameron, A. Cuzzocrea, F. Jiang, C.K. Leung. Effectively and efficiently mining frequent patterns from dense graph streams on disk. Procedia Computer Science, 35 (2014), pp. 338-347. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).en_US
dc.description.abstractIn this paper, we focus on dense graph streams, which can be generated in various applications ranging from sensor networks to social networks, from bio-informatics to chemical informatics. We also investigate the problem of effectively and efficiently mining frequent patterns from such streaming data, in the targeted case of dealing with limited memory environments so that disk support is required. This setting occurs frequently (e.g., in mobile applications/systems) and is gaining momentum even in advanced computational settings where social networks are the main representative. Inspired by this problem, we propose (i) a specialized data structure called DSMatrix, which captures important data from dense graph streams onto the disk directly and (ii) stream mining algorithms that make use of such structure in order to mine frequent patterns effectively and efficiently. Experimental results clearly confirm the benefits of our approach.en_US
dc.description.sponsorshipNatural Sciences and Engineering Research Council of Canada (NSERC); University of Manitobaen_US
dc.identifier.citationP. Braun, J.J. Cameron, A. Cuzzocrea, F. Jiang, C.K. Leung. Effectively and efficiently mining frequent patterns from dense graph streams on disk. Procedia Computer Science, 35 (2014), pp. 338-347.en_US
dc.identifier.doihttp://dx.doi.org/10.1016/j.procs.2014.08.114
dc.identifier.urihttp://hdl.handle.net/1993/32124
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsopen accessen_US
dc.subjectdata miningen_US
dc.subjectfrequent pattern miningen_US
dc.subjectgraph streamsen_US
dc.subjectknowledge-based and intelligent information & engineering systemsen_US
dc.subjectknowledge discoveryen_US
dc.subjectlimited memoryen_US
dc.subjectstream miningen_US
dc.titleEffectively and efficiently mining frequent patterns from dense graph streams on disken_US
dc.typeArticleen_US
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