Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6900191 | Procedia Computer Science | 2018 | 5 Pages |
Abstract
Human contacts prediction is a challenging task in mobile social networks. In this paper, we extract some new features to predict human contacts and propose a new human contacts prediction method which is suitable for dynamic networks. The method first trains a classifier for each time period and assigns different weights to the classifiers of each time period. Then, an ensemble result of all the classifiers is used to predict human contacts. The experimental results show that our proposed method is efficient.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Baoling Wu, Feng Zeng, Wenjia Li,