Community recommendation in social network using strong friends and quasi-clique approach

Anjum Ibna Matin, Sawgath Jahan, M. R. Huq
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引用次数: 5

Abstract

A social networking service is a platform to build relations among people who share interests, activities, backgrounds or real-life connections. Communities in a social network are the gathering places for the people with common interest. Social network analysis is in high demand now a days for the increasing number of users. They involve themselves into different communities. They share post, their views, what they like etc. in communities. So it is important for them to find suitable communities where they have common factors like friends, followers and their activities etc. In this paper, we propose a technique for recommending a community in social network like Facebook, Twitter etc. Finding strong friends from a user's friend list and using clique and quasi-clique concepts introduced in graph mining, we recommend suitable communities for a user in a social network.
基于强朋友和准小团体方法的社交网络社区推荐
社交网络服务是一个在有共同兴趣、活动、背景或现实生活联系的人们之间建立关系的平台。社交网络中的社区是具有共同兴趣的人们的聚集地。随着用户数量的不断增加,对社交网络分析的需求越来越大。他们参与到不同的社区中。他们在社区中分享帖子、观点、喜欢的东西等。所以对他们来说,找到合适的社区是很重要的,在那里他们有共同的因素,如朋友,追随者和他们的活动等。本文提出了一种在Facebook、Twitter等社交网络中推荐社区的技术。从用户的朋友列表中寻找强大的朋友,并使用图挖掘中引入的派系和准派系概念,我们为社交网络中的用户推荐合适的社区。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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