For instance, network embedding methods such as DeepWalk (Perozzi et al., 2014) primarily encode graph structure information, while knowledge embedding methods such as TransE (Bordes et al., 2013) usually focus on triples information, we can flexibly use one of them or merge them together.
we link the detected entity names in sentences to the Freebase5M (Bordes et al., 2015) by n-gram text matching, and use the DeepWalk and TransE embeddings of linked entity candidates denoted as {e 1,1 , e 1,2 , .