Research Article
Graphical Approach for Social Network Mining
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 127 - Issue 7 |
| Published: October 2015 |
| Authors: Priyanka Asrani, Shradha Randad, Sneha Wadhwa, Manisha Gahirwal |
10.5120/ijca2015903616
|
Priyanka Asrani, Shradha Randad, Sneha Wadhwa, Manisha Gahirwal . Graphical Approach for Social Network Mining. International Journal of Computer Applications. 127, 7 (October 2015), 12-15. DOI=10.5120/ijca2015903616
@article{ 10.5120/ijca2015903616,
author = { Priyanka Asrani,Shradha Randad,Sneha Wadhwa,Manisha Gahirwal },
title = { Graphical Approach for Social Network Mining },
journal = { International Journal of Computer Applications },
year = { 2015 },
volume = { 127 },
number = { 7 },
pages = { 12-15 },
doi = { 10.5120/ijca2015903616 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2015
%A Priyanka Asrani
%A Shradha Randad
%A Sneha Wadhwa
%A Manisha Gahirwal
%T Graphical Approach for Social Network Mining%T
%J International Journal of Computer Applications
%V 127
%N 7
%P 12-15
%R 10.5120/ijca2015903616
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Social Networking sites are a rage in today’s world. Its importance has transcended the sole purpose of keeping in touch. In the quest of outweighing their contemporaries, social networking websites in today’s world needs to incorporate new and interesting features to have an edge. Data Mining plays an important role in providing many such features. The social network structure consisting of numerous users can be best implemented using a graph data structure. It takes into consideration the data regarding various forms of interaction between two users to compute their association. The basic features such as friend suggestions, community suggestions, etc. have been incorporated. Also, commercial features such as targeted advertisement have been included.
References
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