Deep Learning is a cutting edge technology that has revolutionized AI and Machine Learning in the past few years. It is an advanced technique that can automatically discover patterns from large amounts of data. Common examples of Deep Learning that we all use on a daily basis include speech recognition (e.g. Siri, Alexa etc.) and movie or music recommendation (e.g. Netflix, Spotify). Even your daily Google searches are powered by Deep Learning.

Within every domain that comes with a lot of data, Deep Learning can improve and empower business processes. HR and Talent Acquisition (TA) is no exception. In this article, we will shortly discuss three examples of potential applications of Deep Learning in the HR or TA domain. If you’re interested in learning more about Deep Learning and how it can benefit your TA processes, please join our webinar.

1- CV Parsing

CV Parsing is a crucial first step for TA: properly understanding and coding CVs is essential for searching, matching or data analytics. CV Parsing is considered a commodity nowadays, but under the hood, there are elaborate, complex language models based on Deep Learning. In 2017, Textkernel released the first Deep Learning-based CV parser with a very big improvement in parsing accuracy. Language models based on this technique are much more rich and subtle than simpler language models, and therefore “understanding” the text in a CV is much easier.

2- Knowledge Mining

Because Deep Learning allows algorithms to have a deeper “understanding” of what language means, that also means we can apply it to gather domain knowledge from data. For example, the algorithm can learn that good communication skills are important for a sales job. It can also understand very specialized skills, and how they relate to each other, like big data skills ‘Hadoop’ and ‘HDFS’ being related. Once incorporated in products like Textkernel’ Search&Match, recruiters can find and match the right candidates or jobs without knowing this specialized knowledge.

3- Matching people and jobs

A Deep Learning algorithm can learn which people in your database are good candidates for a given job. Based on past data, Deep Learning models can be taught to understand what are important elements for a good match. The advantage that Deep Learning can bring for this application is that it grasps subtleties much better than a keyword-based matching system.


These are just three examples of how Deep Learning can empower TA processes. If this article piqued your curiosity, please join us at our webinar on June 10th. In this webinar, we will explain in Layman’s terms how Deep Learning works and how it can be applied to the TA domain. No prior technical experience or knowledge required.


This blog post was written by Vincent Slot, team lead Search R&D and Mihai Rotaru, head of R&D at Textkernel.

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EngageX 2020

Textkernel is excited to present at EngageX | Digital Event!

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Embracing online events – Textkernel Platinum sponsor at the first online EngageX!

With the 2020 events calendar turned on its head, Bullhorn EngageX promises to bring you everything you love about the Engage series of staffing conferences in an immersive online format.

Here’s what you can look forward to

Our CEO, Gerard Mulder, will participate in the Marketplace showdown. We’ll be hosting a discussion group. And of course, our team will be ‘walking’ around the virtual conference room to discuss today’s challenging times in staffing or answer any questions you might have. We’d love to hear from you!

So whether you’re looking to improve your workflow and boost recruiter efficiency, struggling to find business opportunities in today’s economic downturn, or having trouble placing all your candidates our AI-powered solutions can help your business not just survive 2020, but thrive!

Discover the full Textkernel offering in Bullhorn.