In this talk, we will consider current embedding algorithms from the perspective of knowledge extraction.
I will present practical use cases for the construction of knowledge graphs and ontologies.
Beyond word embeddings, the talk also encompasses sentence and document embeddings.
We will also see that embeddings are also a highly useful tool for dynamic data analytics – by capturing changes over time that happen in the vector space, they allow us to monitor and interpret new or updated pieces of knowledge.
