Cart (Loading....) | Create Account
Close category search window
 

Link prediction and classification in social networks and its application in healthcare

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

5 Author(s)
Almansoori, W. ; EMS, Alberta Health Services, Calgary, AB, Canada ; Shang Gao ; Jarada, T.M. ; Alhajj, R.
more authors

Prediction is one of the most attractive aspects in data mining. Link prediction has recently attracted the attention of many researchers as an effective technique to be used in social network analysis to understand the associations between nodes in social communities. It has been shown in the literature that the link prediction technique is limited to predict the existence of the links in the future. To the best of our knowledge, none of the previous works in this area has explored the prediction of the links that could disappear in the future. In this paper, we propose a link prediction model that is capable of predicting link that might exist and links that may disappear in the future. The model has been successfully applied in two different domains, namely health care and stock market. We have tested our model using different classifiers and the reported results are encouraging.

Published in:

Information Reuse and Integration (IRI), 2011 IEEE International Conference on

Date of Conference:

3-5 Aug. 2011

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.