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dc.contributor.authorYu, Ching-Huaen_US
dc.contributor.authorPeng, Wen-Chihen_US
dc.contributor.authorLee, Wang-Chienen_US
dc.date.accessioned2014-12-08T15:02:29Z-
dc.date.available2014-12-08T15:02:29Z-
dc.date.issued2008en_US
dc.identifier.isbn978-0-7695-3434-3en_US
dc.identifier.urihttp://hdl.handle.net/11536/1153-
dc.identifier.urihttp://dx.doi.org/10.1109/ICPADS.2008.93en_US
dc.description.abstractMost social networks exhibit community structures, in which nodes are tightly connected to each other within a community but only loosely connected to nodes in other communities. Researches on community mining have received a lot of attention; however, most of them are based on a centralized system model and thus not applicable to the distributed model of P2P networks. In this paper, we propose a distributed: community mining algorithm, namely Asynchronous Clustering and Merging scheme (ACM), for computing environments. Due to the dynamic and distributed nature of P2P networks, The ACM scheme employs an asynchronous strategy such that local clustering is executed without requiring an expensive global clustering to be performed in asynchronous fashion. Experimental results show that ACM is able to discover community structures with high quality while outperforming the existing approaches.en_US
dc.language.isoen_USen_US
dc.subjectDistributed node clusteringen_US
dc.subjectconnected graphen_US
dc.subjectpeer-to-peer networksen_US
dc.titleMining Community Structures in Peer-to-Peer Environmentsen_US
dc.typeProceedings Paperen_US
dc.identifier.doi10.1109/ICPADS.2008.93en_US
dc.identifier.journalPROCEEDINGS OF THE 2008 14TH IEEE INTERNATIONAL CONFERENCE ON PARALLEL AND DISTRIBUTED SYSTEMSen_US
dc.citation.spage351en_US
dc.citation.epage358en_US
dc.contributor.department交大名義發表zh_TW
dc.contributor.departmentNational Chiao Tung Universityen_US
dc.identifier.wosnumberWOS:000263157700044-
Appears in Collections:Conferences Paper


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