These algorithms traverse over the relations and nodes in a large knowledge base such as WordNet (Miller, 1995) or taxonomies built from Wikipedia links (Cucerzan, 2007) to uncover relationships between the nodes in the knowledge base.
the effectiveness of shallow neural networks in learning word similarity, as shown by the popular Word2Vec and GloVe models (Mikolov et al., 2013;Pennington et al., 2014), rapidly replaced traditional graph-based methods for word similarity and prediction tasks.