Using Graph Clustering for Community Discovery in Web-Based Social Networks

摘要：

　　Knowledge discovery in social networks is not a trivial task.Often research in this context uses concepts of data mining, social network analysis,trust discovery and sentiment analysis.The connected network of people is generally represented by a directed graph (social graph), whose formulation includes representing people as nodes and their relationships as edges, which also can be labeled to describe the relationship (eg.friend, son and girlfriend).This environment of connected nodes behaves like a dynamic network, whose nodes and connections are constantly being updated.People tend to communicate or relate better with other people who have a common or similar way of thinking, which generates groups of people with common interests, the communities.This paper studies the use of a graph clustering approach, the Coring Method, originally employed in image segmentation task, in order to be applied in the context of community discovery on a social network environment.

关键词： Graph Clustering Community Discovery Data Mining Web-based Social Networks

作者: Jackson Gomes Souza Edeilson Milhomem Silva Parcilene Fernandes Brito José Alfredo F.Costa Ana Carolina Salgado Silvio R.L.Meira

作者单位: Department of Computing, Centro Universitário Luterano de Palmas,Av.Theotonio Segurado, 1501 Sul, Pa Center of Technology, Federal University of Rio Grande do Norte, RN, Brazil Center of Informatics, Federal University of Pernambuco, PE, Brazil

会议类型: 国际会议

会议名称: 4th international Conference,ICSI2013(第4届群体智能国际会议)

会议地点: 哈尔滨

会议语种:英文

页码: 120-129

在线出版日期: 2013-06-12（万方平台首次上网日期，不代表论文的发表时间）