{"title":"基于强朋友和准小团体方法的社交网络社区推荐","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":"{\"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}","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}
Community recommendation in social network using strong friends and quasi-clique approach
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.