Batch Mode Active Learning for Node Classification in Assortative and Disassortative Networks
Active learning for networked data that focuses on predicting the labels of other nodes accurately by knowing the labels of a small subset of nodes is attracting more and more researchers because it is very useful especially in cases, where labeled data are expensive to obtain. However, most existin...
Main Authors: | Shuqiu Ping, Dayou Liu, Bo Yang, Yungang Zhu, Hechang Chen, Zheng Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2018-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8141855/ |
Similar Items
-
Community Detection in Signed Networks Based on the Signed Stochastic Block Model and Exact ICL
by: Shuqiu Ping, et al.
Published: (2019-01-01) -
A Study on the Relationship between Connecting Different Types of Nodes and Disassortativity by Degree
by: Chengdong Dong
Published: (2010-01-01) -
Second-Order Markov Assumption Based Bayes Classifier for Networked Data With Heterophily
by: Sa Dong, et al.
Published: (2019-01-01) -
Graph-based generation of a meta-learning search space
by: Jankowski Norbert
Published: (2012-09-01) -
Special Issue on Advanced Learning Methods for Complex Data
by: Maurizio Atzori, et al.
Published: (2018-12-01)