Prediction of Attributes and Links in Temporal Social Networks

The analysis of social networks often assumes the time invariant scenario while in practice node attributes and links in such networks often evolve over time. In this paper, we propose a new method to predict node attributes and links in temporal networks.

• Type: Conference
• Year: 2010
• Where: ECAI
• Authors: Vladimir Ouzienko, Yuhong Guo, Zoran Obradovic
• Keywords: Artificial Intelligence, ECAI 2010, Node Attributes, Practice Node Attributes, Time Invariant Scenario