DocumentCode :
251329
Title :
Community recommendation in social network using strong friends and quasi-clique approach
Author :
Matin, Anjum Ibna ; Jahan, Sawgath ; Huq, Mohammad Rezwanul
Author_Institution :
Dept. of Comput. Sci. & Eng., Islamic Univ. of Technol., Gazipur, Bangladesh
fYear :
2014
fDate :
20-22 Dec. 2014
Firstpage :
453
Lastpage :
456
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.
Keywords :
data mining; graph theory; recommender systems; social networking (online); community recommendation; graph mining; quasiclique approach; social networking service; Communities; Databases; Facebook; Forecasting; Lifting equipment; Positron emission tomography; clique; data mining; quasi-clique; social media; social network analysis and mining; strong friends;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Computer Engineering (ICECE), 2014 International Conference on
Conference_Location :
Dhaka
Print_ISBN :
978-1-4799-4167-4
Type :
conf
DOI :
10.1109/ICECE.2014.7026937
Filename :
7026937
Link To Document :
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