1. How can semantic searching and matching transform your recruitment process?

Our semantic searching and matching technology can empower many of your companies processes.

• It search in your past applicants to reduce recruitment cost
• It identify the best candidates in the external database
• It rank your incoming candidates to reduce time-to-hire
• It sent job recommendations to improve your candidates experience
• It enable you to match your employees skills with open jobs

2. How does semantic searching and matching work?

Professional skills are analyzed and evaluated by calculation algorithms, to then be accepted or rejected based on parameters of professional proximity.

The algorithm runs an extraction of the professional tags contained in the job offers; then it compares them with the skills found in the candidates’ CVs and displays the list of candidates sorted by degree of compatibility for the selected talent pool.

3. How is our semantic engine born?

Ten years ago when we created our semantic engine, the ” professional tags” were searched and analyzed manually, but later, with a machine learning project, the work has been handed over to software.

For each single profession, the software has the task of indicating and identifying the jobs that have not yet been considered.

The software does not choose independently, but suggests.

Accepting or rejecting a task will create additional rules that the machine will learn for future suggestions.

The end result is a huge amount of work, we talk about big data, that can be done automatically by the machine. We are talking about machine learning because our semantic engine learns and improves every day.