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

Anjum Ibna Matin, Sawgath Jahan, M. R. Huq
{"title":"Community recommendation in social network using strong friends and quasi-clique approach","authors":"Anjum Ibna Matin, Sawgath Jahan, M. R. Huq","doi":"10.1109/ICECE.2014.7026937","DOIUrl":null,"url":null,"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.","PeriodicalId":335492,"journal":{"name":"8th International Conference on Electrical and Computer Engineering","volume":"83 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"8th International Conference on Electrical and Computer Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECE.2014.7026937","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Empirical prediction of optical transitions in metallic armchair SWCNTs Dynamics of fullerene self-insertion into carbon nanotubes in water Diffusion tensor based global tractography of human brain fiber bundles Biomass quality analysis for power generation Video-based affinity group detection using trajectories of multiple subjects
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1