Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/2374
Full metadata record
DC FieldValueLanguage
dc.contributor.authorPadma Priya B-
dc.contributor.authorSathiyakumari K-
dc.date.accessioned2020-12-24T05:12:23Z-
dc.date.available2020-12-24T05:12:23Z-
dc.date.issued2013-07-
dc.identifier.issn2277-9655-
dc.identifier.urihttp://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.404.1633&rep=rep1&type=pdf-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/2374-
dc.description.abstractIn this paper we present a large Scale Community detection and analysis of Facebook, which gathers more than one billion active users in 2012. Characteristics of this online social network have been widely researched over these years. Facebook has affected the social life and activity of people in various ways. One major fact in today's technical world, people are very active users of Online Social Networks. They share every details of their day to day life and are in touch with their loved ones no matter in which part of the world they live. The impact is considerably taken into account as this online Social Network play a very important role in people lives. We study the structural properties of these samples in order to discover their community Structure. Here two Clustering algorithms are used to discover the communities in Complex networks and is compared.en_US
dc.language.isoenen_US
dc.publisherInternational Journal of Engineering Sciences & Research Technologyen_US
dc.subjectData miningen_US
dc.subjectComplex Networksen_US
dc.subjectCommunity Miningen_US
dc.subjectCommunity Detectionen_US
dc.titleA SURVEY OF COMMUNITY DETECTION IN ONLINE SOCIAL NETWORKen_US
dc.typeArticleen_US
Appears in Collections:International Journals

Files in This Item:
File Description SizeFormat 
A SURVEY OF COMMUNITY DETECTION IN ONLINE SOCIAL NETWORK.docx10.51 kBMicrosoft Word XMLView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.