Since its publication in 2016 by Aditya Grover and Jure Leskovec, Node2vec has become the go-to algorithm to easily compute embeddings for nodes in a graph/network. Working with embeddings has […]
Knowledge Graph
Linked Data – Past, present (2019) and future
About two weeks ago, I had the pleasure to give a talk at the ESSnet (European Statistical System network) final meeting held in Sofia, Bulgaria. My presentation was about the […]
Knowledge Graph Features and Explanation
Although latent feature models such as TransE are demonstrating state-of-the-art performance in the task of link prediction in knowledge graphs, they act as a black box. Latent feature models rely […]
Translating Embeddings (TransE)
In this post I present Translating Embeddings (TransE), a method for the prediction of missing relationships in knowledge graphs. Rather than digging into the mathematics, I focus on presenting the […]