The Job8 Summit Interview Series – Jakub Zavrel

I have known Jakub and his company Textkernel for 9 years. I met them when I was with and, at the time, their technology blow me away. Over the last 9 years the business has grown its product portfolio and geographical reach.


I’m personally delighted that Jakub is joining us at the EJBS 2013; he gets the big data issue, semantic search and how to build products that deliver solutions as opposed to creating more problems.

So in true Jobg8 spirit, we asked those tough questions.

Q – Could you explain a little bit about who Textkernel are and what you do?

At Textkernel we are trying to solve the problem that the labour market is inefficient because of a language and information gap between job seekers and employers. Job seekers have a hard time to find a job because they don’t know where to search and how to search, and the same is true to some extent for recruiters looking for candidates.

Search is complicated for both sides, and it shouldn’t be. They communicate with each other in unstructured data with a lot of differences in terminology. And the amount of unstructured data is only increasing. So match-making in automated systems, like job boards and recruitment software, is not always working really well.

By making systems more ‘Semantic’, allowing them to make sense of unstructured big data, Textkernel helps bridge the gap between people and jobs. Textkernel has a very specific expertise in building these extractions, search & match engines for a multi-lingual world and aims to provide these to all parties in the labour market.

We also crawl jobs ( and make all of that data available for lead generation, labour market analytics, matching and recruitment intelligence.

Q – Jakub, we hear a lot about big data, in the simplest terms “what is it and what does it mean?” How can the Recruitment Industry use “big data?”

Big Data is, roughly speaking, data from multiple sources that comes in such volumes and at such a speed that it is no longer possible to analyse it with conventional spreadsheets or databases. It can, for example, be click data from a high traffic job board, combined with data about the content on that site, combined with unstructured social network interactions and content of its visitors, or metrics from operational HR systems.

It can be the raw material for improving processes and discovering hidden correlations, so it has a lot of potential to change and disrupt current business models, including recruitment and talent management. Big Data is also a big buzzword and currently in HR many people use the term to refer to doing any kind of statistical or analytical work on HR related data.

Personally, I think the major promise of Big Data for recruitment and HR is in being able to characterise people and jobs in terms of the content and behaviour so as to better understand them more and allow for better matchmaking in the labour market.

 Q – What can Job boards do to use big data and can it become a part of their offering?

I think the key task for Job boards is to collect information about who their job seekers are and what the jobs on their board are all about, in order to give both sides a better service and search relevance. Good relevance is going to become the number one competitive advantage for any job board.

Q – Semantic Search – could you give a simple definition?

The simplest definition of Semantic Search is: search that gives you what you mean, instead of what you type.

Q – Does it really do what people claim?

Current state-of-the-art semantic search engines for jobs and people beat simple keyword search approaches hands down. So, yes, it is a big advantage to use it. But we are not *done* yet.

Obviously humans still beat computers at reading and understanding the meaning of questions and of text. But humans have a hard time reading through very large collections of documents, hundreds, thousands or millions.

So if you are looking for the best job or candidate in the market, I’d rather have good, semantically capable tools than a last generation search engine which forces me to guess which keywords the job or candidate just might have used.

Q – What is more important “Big Data or Semantic Search?” Or am I being stupid in that they are either different or you need both to drill into and analyse the data?

Big Data and Semantic Search go hand in hand. You cannot deal with unstructured data if you cannot use big data analytics to make sense of it and vice versa.

Q – What next for Textkernel?

We are seeing semantic technology starting to move into the main stream of recruitment. That’s great for our business and the business of our clients.

But our task will not be done until every job seeker and recruiter can truly find what they mean in the job market. We love to build strong partnerships with our customers that allow us to take that journey together.

There’s still a lot of R&D and productisation to be done.

My thanks to Jakub for some great insights and answer. As an ex-job boarder our real customer are the job seekers, they pay the bills and we need to improve their experience.

Keith Robinson is a regular contributor to the Jobg8 blog, co-produces the Jobg8 Summits and works with a range of job boards advising on strategy, NPD, marketing and NBD across Europe

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