  This study focuses on the prediction of missing six semantic relations (such
as is_a and has_part) between two given nodes in RezoJDM a French
lexical-semantic network. The output of this prediction is a set of pairs in
which the first entries are semantic relations and the second entries are the
probabilities of existence of such relations. Due to the statement of the
problem we choose the random forest (RF) predictor classifier approach to
tackle this problem. We take for granted the existing semantic relations, for
training/test dataset, gathered and validated by crowdsourcing. We describe how
all of the mentioned ideas can be followed after using the node2vec approach in
the feature extraction phase. We show how this approach can lead to acceptable
results.
