Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/32461
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dc.contributor.authorMoosa, J-
dc.contributor.authorAwad, W-
dc.contributor.authorKalganova, T-
dc.coverage.spatialManama, Bahrain-
dc.date.accessioned2025-12-05T12:20:37Z-
dc.date.available2025-12-05T12:20:37Z-
dc.date.issued2020-02-10-
dc.identifierORCiD: Tatiana Kalganova https://orcid.org/0000-0003-4859-7152-
dc.identifier.citationMoosa, J., Awad, W. and Kalganova, T. (2020) 'Intelligent Community Detection: Review', 11th Annual PhD without Residence Doctoral Symposium (PwR - 2020), Manama, Bahrain, 10-11 February, pp. 1 - 7.en_US
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/32461-
dc.descriptionA recording of the conference paper presented by Jenan Moosa at the 11th Annual PhD without Residence Doctoral Symposium (PwR - 2020), Manama, Bahrain, 10-11 February 2020 is available on YouTube at: https://www.youtube.com/watch?v=oIi69hA8x2Y . A copy of the paper is available online at SSRN: https://ssrn.com/abstract=3659107 .-
dc.description.abstractAn emerging multidisciplinary field nowadays is graph mining; which is basically a form of data mining that deals with graphs instead of normal data, (Cook & Holder, 2006) it intends to discover repetitive sub-graphs and interesting patterns that occurs in the input graph. This research is focusing on community detection using graph mining techniques; the objectives are to study the existing methods used to solve this problem by comparing the evaluation parameters, and then develop a method for community detection in social networks, which meets the criteria identified for assessing a good algorithm. Various techniques of graph mining will be tested to determine wither it can meet the identified criteria.en_US
dc.format.extent1 - 7-
dc.format.mediumElectronic-
dc.language.isoen_USen_US
dc.relation.urihttps://www.youtube.com/watch?v=oIi69hA8x2Y-
dc.relation.urihttps://www.ahlia.edu.bh/events/the-11-annual-pwr-doctoral-symposium/-
dc.relation.urihttps://ssrn.com/abstract=3659107-
dc.source11th Annual PhD without Residence Doctoral Symposium (PwR - 2020)-
dc.subjectintelligent communityen_US
dc.subjectgraph miningen_US
dc.subjectcommunity detectionen_US
dc.titleIntelligent Community Detection: Reviewen_US
dc.typeConference Paperen_US
pubs.finish-date2020-02-11-
pubs.finish-date2020-02-11-
pubs.start-date2020-02-10-
pubs.start-date2020-02-10-
dc.rights.holderThe Author(s)-
Appears in Collections:Dept of Electronic and Electrical Engineering Research Papers

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