General Description: This project implementation is in Python. It has the implementations for several unsupervised contact predictors to infer missing contacts in a mobile social setting by exploiting the known properties of contact graphs . We define a contact graph to be a graph in which nodes are people and edges represent people physical contacts.
Code Input: It uses the Infocom 2005 and 2006 human mobility traces collected by iMotes.
Code Output: It outputs the accuracies of different contact predictors.
Project Goal: The main goal was to predict who is the next person whom you will visit.
Implementation period: July - August 2010.
The implemented methods are listed below:
 K. Jahanbakhsh, G.C. Shoja, V. King, Human Contact Prediction Using Contact Graph Inference, CPSCom 2010, Hangzhou, China.
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