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dc.contributor.authorHao, F.*
dc.contributor.authorYau, S.S.*
dc.contributor.authorMin, Geyong*
dc.contributor.authorYang, L.T.*
dc.date.accessioned2016-11-23T18:25:38Z
dc.date.available2016-11-23T18:25:38Z
dc.date.issued2014
dc.identifier.citationHao F, Yau SS, Min G et al (2014) Detecting k-Balanced Trusted Cliques in Signed Social Networks. IEEE Internet Computing. 18(2): 24-31.
dc.identifier.urihttp://hdl.handle.net/10454/10645
dc.descriptionNo
dc.description.abstractk-Clique detection enables computer scientists and sociologists to analyze social networks' latent structure and thus understand their structural and functional properties. However, the existing k-clique-detection approaches are not applicable to signed social networks directly because of positive and negative links. The authors' approach to detecting k-balanced trusted cliques in such networks bases the detection algorithm on formal context analysis. It constructs formal contexts using the modified adjacency matrix after converting a signed social network into an unweighted one. Experimental results demonstrate that their algorithm can efficiently identify the trusted cliques.
dc.relation.isreferencedbyhttps://doi.org/10.1109/MIC.2014.25
dc.subjectSigned social networks; FCA; Equiconcept; Trusted cliques; Trust managements; Network security
dc.titleDetecting k-Balanced Trusted Cliques in Signed Social Networks
dc.status.refereedYes
dc.typeArticle
dc.type.versionNo full-text available in the repository


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