- [Instructor] The third step is to build a knowledge base
and feed it with data.
You can analyze large volumes of text documents
or the machine learning
and map them to a knowledge graph.
Here we see (indistinct)
and his relations to coworkers,
as well as recommendations for new projects and roles.
The system has analyzed the skills off the employee
and recommends suitable projects for him.
The system displays open positions
and the skills that are
required in these projects.
If you have created a taxonomy
and created an ontology,
you want to build up a knowledge base.
Let's look at this application
that supports the staffing process for projects.
It is a Human Resource Recommender system based on semantic
technologies with the help of the tool pool party.
We lock in as the sample, you, the keys,
The knowledge graph behind this application is based
on a taxonomy for skills.
For example IT jobs.
The European database for this domain contains more
than 13 thousand skills and competencies.