CCGraMi: An Effective Method for Mining Frequent Subgraphs in a Single Large Graph

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dc.contributor.authorNguyen, Lam B. Q.
dc.contributor.authorZelinka, Ivan
dc.contributor.authorDiep, Quoc Bao
dc.coverage.issue2cs
dc.coverage.volume27cs
dc.date.accessioned2022-01-26T08:21:53Z
dc.date.available2022-01-26T08:21:53Z
dc.date.issued2021-12-21cs
dc.description.abstractIn modern applications, large graphs are usually applied in the simulation and analysis of large complex systems such as social networks, computer networks, maps, traffic networks. Therefore, graph mining is also an interesting subject attracting many researchers. Among them, frequent subgraph mining in a single large graph is one of the most important branches of graph mining, it is defined as finding all subgraphs whose occurrences in a dataset are greater than or equal to a given frequency threshold. In which, the GraMi algorithm is considered the state of the art approach and many algorithms have been proposed to improve this algorithm. In 2020, the SoGraMi algorithm was proposed to optimize the GraMi algorithm and presented an outstanding performance in terms of runtime and storage space. In this paper, we propose a new algorithm to improve SoGraMi based on connected components, called CCGraMi (Connected Components GraMi). Our experiments on four real datasets (both directed and undirected) show that the proposed algorithm outperforms SoGraMi in terms of running time as well as memory requirements.en
dc.formattextcs
dc.format.extent90-99cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationMendel. 2021 vol. 27, č. 2, s. 90-99. ISSN 1803-3814cs
dc.identifier.doi10.13164/mendel.2021.2.090en
dc.identifier.issn2571-3701
dc.identifier.issn1803-3814
dc.identifier.urihttp://hdl.handle.net/11012/203385
dc.language.isoencs
dc.publisherInstitute of Automation and Computer Science, Brno University of Technologycs
dc.relation.ispartofMendelcs
dc.relation.urihttps://mendel-journal.org/index.php/mendel/article/view/162cs
dc.rightsCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International licenseen
dc.rights.accessopenAccessen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0en
dc.subjectData miningen
dc.subjectPruning techniquesen
dc.subjectSingle large graphen
dc.subjectSubgraph miningen
dc.subjectWeighted subgraphen
dc.titleCCGraMi: An Effective Method for Mining Frequent Subgraphs in a Single Large Graphen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta strojního inženýrstvícs
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Vol. 27, No. 2