… -item relatedness for item recommendation through property-specific knowledge graph
embeddings… analyze the behaviour of knowledge graph embeddings computed using node2vec: …

… [14] provides a Review of graph embedding based … embeddings in the same baseline
recommender using the MovieLens-100K dataset, knowledge graph embeddings using node2vec …

… the traditional embedding layer with node2vec graph embedding … , Graph embeddings will
be able incorporate user and item … The work in [16] provides a Review of graph embedding …

… , node2vec) that we have applied to the recommendation problem … recommendations from
a knowledge graph? We show that node2vec can be applied directly on the knowledge graph …

… recommended items. The above studies have demonstrated that incorporating recommendation
algorithms based on knowledge graph … used node2vec on the knowledge graph to each …

… approach (node2vec) to predict missing relations in a knowledge graph previously … the
knowledge graph has been designed, we adopt the node embedding to infer new knowledge (…

… on different realworld knowledge graphs and compared it with … embeddings in the context
of user-item recommendations. … like node2vec have proposed ways to learn embeddings for …

… of recommender systems and knowledge graphs are first briefly introduced, … knowledge
graph embedding and recommender systems. In addition, a series of related recommendation …

… in the recommendation systems, collaborates users and items into … , thus regulating the user
and item feature embedding. … First, we review Word2vec and its extensions. Since Mikolov …

… node2vec [10] extends DeepWalk by relaxing the definition of neighborhoods of vertices.
It proposes a biased random walk procedure that introduces a search bias that controls the …