By Topic

Task-Oriented Social Ego Network Generation via Dynamic Collaborator Selection

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Xing Fang ; Dept. of Comput. Sci., North Carolina A&T State Univ., Greensboro, NC, USA ; Zhan, J.

Social networks are social structures derived from general human societies based upon certain scope or relationships. People in social networks, rather than behaving randomly, are highly organized and cooperative. To study evolutions of social networks, existing random graph theories only provide global views on network evolutions. Nevertheless, the evolutions of a social network should be examined from a local point of view. That is we can claim that someone's social network has evolved, if and only if the network is indeed evolved from the person's perspective. Hence, in this paper, we introduce the concept of social ego network. We propose two dynamic collaborator selection methods for the Task-Oriented Social Ego Network Generation process, which is believed to be the key process of social ego network evolution. We also conduct experimental simulations for our proposed methods.

Published in:

Privacy, Security, Risk and Trust (PASSAT), 2012 International Conference on and 2012 International Confernece on Social Computing (SocialCom)

Date of Conference:

3-5 Sept. 2012