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DC Field | Value | Language |
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dc.contributor.author | Padma Priya B | - |
dc.contributor.author | Sathiyakumari K | - |
dc.date.accessioned | 2020-12-24T05:12:23Z | - |
dc.date.available | 2020-12-24T05:12:23Z | - |
dc.date.issued | 2013-07 | - |
dc.identifier.issn | 2277-9655 | - |
dc.identifier.uri | http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.404.1633&rep=rep1&type=pdf | - |
dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/2374 | - |
dc.description.abstract | In 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.iso | en | en_US |
dc.publisher | International Journal of Engineering Sciences & Research Technology | en_US |
dc.subject | Data mining | en_US |
dc.subject | Complex Networks | en_US |
dc.subject | Community Mining | en_US |
dc.subject | Community Detection | en_US |
dc.title | A SURVEY OF COMMUNITY DETECTION IN ONLINE SOCIAL NETWORK | en_US |
dc.type | Article | en_US |
Appears in Collections: | International Journals |
Files in This Item:
File | Description | Size | Format | |
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A SURVEY OF COMMUNITY DETECTION IN ONLINE SOCIAL NETWORK.docx | 10.51 kB | Microsoft Word XML | View/Open |
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