WeFreS: weighted frequent subgraph mining in a single large graph

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dc.contributor.authorAshraf, Nahian
dc.contributor.authorHaque, Riddho Ridwanul
dc.contributor.authorIslam, Md. Ashraful
dc.contributor.authorAhmed, Chowdhury Farhan
dc.contributor.authorLeung, Carson K.
dc.contributor.authorMai, Jiaxing Jason
dc.contributor.authorWodi, Bryan H.
dc.date.accessioned2020-03-09T20:14:09Z
dc.date.available2020-03-09T20:14:09Z
dc.date.issued2019-07
dc.date.submitted2020-03-03T00:22:30Zen_US
dc.description.abstractConsidering edge weights during frequent subgraph mining can help us discover more interesting and useful subgraph patterns when compared to its unweighted counterparts. Although some recent works have proposed weight adaptation in frequent subgraph mining from transactional graph databases, the consideration of edge-weights in mining subgraph patterns from single large graphs is mostly unexplored. However, such graph structures appear frequently, with instances being found in social networks, citation and collaboration graphs, chemical and biological networks, etc. In this paper, we propose WeFreS, an efficient algorithm for mining weighted frequent subgraphs in edge-weighted single large graphs. WeFreS takes into consideration the weight, or significance of the interactions between different types of entities, and only outputs subgraphs whose weighted support is greater than a given user-defined threshold. The resulting subgraph patterns are both frequent and significant from the application perspective. Moreover, for efficiency, WeFreS is also equipped with various pruning techniques and optimizations.en_US
dc.description.sponsorshipNatural Sciences and Engineering Research Council of Canada (NSERC); University of Manitobaen_US
dc.identifier.citationAshraf, N., Haque, R.R., Islam, M.A., Ahmed, C.F., Leung, C.K., Mai, J.J., Wodi, B.H.: WeFreS: weighted frequent subgraph mining in a single large graph. In: ICDM 2019, pp. 201-215 (2019)en_US
dc.identifier.isbn978-3-942952-60-6
dc.identifier.issn1864-9734
dc.identifier.urihttp://hdl.handle.net/1993/34564
dc.language.isoengen_US
dc.publisheribai publishingen_US
dc.rightsopen accessen_US
dc.subjectSingle large graphen_US
dc.subjectWeighted single large graphen_US
dc.subjectGraph miningen_US
dc.subjectWeighted frequent subgraph miningen_US
dc.titleWeFreS: weighted frequent subgraph mining in a single large graphen_US
dc.typebook parten_US
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Ashraf, N., Haque, R.R., Islam, M.A., Ahmed, C.F., Leung, C.K., Mai, J.J., Wodi, B.H.: WeFreS: weighted frequent subgraph mining in a single large graph. In: ICDM 2019, pp. 201-215 (2019) ICDM 2019 Proceedings, "Advances in Data Mining: Applications and Theoretical Aspects", is an open access proceedings book.
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