基于社交网络的社区发现算法研究  

Analysis of Community Discovery Algorithms Based on Social Communication Networks

作　　者：毋建军[1] 

机构地区：[1]北京政法职业学院信息技术系,北京102628

出　　处：《长春大学学报》2016年第6期35-38,43,共5页Journal of Changchun University

基　　金：北京政法职业学院课题(KYZX201404)

摘　　要：随着社交网络的快速发展及应用,围绕社交网络用户及信息交互自发形成的网络社区已经成为当前社交网络研究领域的重要分支,并取得了许多研究进展及成果,但仍然存在许多挑战及问题。本文从网络社区研究的网络结构、网络信息、时间三个重要因素考虑,在网络社区的定义、特性的基础上,分类、对比了典型的社区发现模型、算法及社区划分评价方法,并对其存在的问题及未来发展方向进行了分析探讨。Along with the rapid development and application of social communication network,online community centering on social communication network users and information interaction becomes an important branch in the field of social communication network study. Although many results have been made,there are many challenges and problems. Considering network structure,network information and time,this paper analyzes and compares typical community discovery models,algorithms and evaluation methods based on the definitions and features of network community,and discusses the problems and future development direction.

关 键 词：社交网络 社区算法 动态社区 SNS分析 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]