Recommender system for community in social network
K. Raghuveer · 2016
1,3,4,5 Department of Information Science and Engineering, The National Institute of Engineering, Mysore, Karnataka 2 Head of the Department, Information Science and Engineering, the National Institute of Engineering, Mysore, Karnataka Abstract Social networking service is a platform builds 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 nowadays 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 using clique and quasi-clique concepts introduced in graph mining and also using user’s area of interest, we recommend suitable communities for a user in a social network. Keywords-social network analysis and mining, data mining, strong friends, social media, clique, quasi-clique.