Technologies, trends and theories:
knowledge at the cutting edge.
Our knowledge base contains information, interesting facts and selected articles on the latest trends and current developments on global labor markets and in the world of semantic technologies relating to human resources and recruitment, occupation (big) data and ontologies / knowledge graphs, job classifications, CV parsing, skills and job matching and much more.
In today’s digital world, computers can analyse competences and work experience faster and more effectively than humans. JANZZsme! powered by ontology transforms data about education, training, work experience and specialisation. Which helps governments and organisations to broaden their talent pool.
If you are in charge at a large international company organisation, institution, government or public employment service, contact email@example.com and we will assist you with our unique AI based talent matching tool. » Read more about: Improve your skills-based matching with JANZZsme! »
To structure large amounts of data, JANZZ.technology combines its ontology (JANZZ.on!) with deep learning models.
JANZZ ontology is the largest and multilingual in the area of occupation data. Therefore, if you are a company, organisation, government/public employment service and would like to empower your data, please write to firstname.lastname@example.org. » Read more about: How can JANZZon! help your data? »
Digitalization, automation and AI pose a great threat to today’s job market that requires constantly changing skills. However, some of the skills are not missing due to the evolution of technology, but rather due to a loss of attractiveness. This is especially the case for positions with an unusually high number of vacancies or such that remain vacant for a long time.
According to the Swiss Skills Shortage Index, “a skills shortage exists if there are more vacancies than job seekers in an occupation.” Last year, » Read more about: Is reskilling and upskilling the real cure for today’s skills shortage? »
Ontologies have been around in artificial intelligence (AI) research for the last 40 years. Just as trends come and go, ontologies too have had their ups and downs. Introduced in the 80s, ontologies became popular in the mid-90s. After machine learning (ML) came on the scene in 2000, the widespread opinion was that in the future every task performed with a computer (by means of AI and ML) could be solved with a smart algorithm. A lot of companies invested heavily in these algorithms hoping to have the next breakthrough in AI. » Read more about: JANZZ ontology – empowering your data and realizing smart applications »
Artificial intelligence (AI) is unquestionably a powerful tool. Its economic value is increasing tremendously and transforming numerous industries such as manufacturing, fintech, healthcare and automobile. Workers in finance and marketing have much success using AI technologies, whereas HR practitioners find it rather hard to integrate these into their daily practices.
Prasanna Tambe, Peter Cappelli and Valery Yakubovich state in their research: “there are systemic and structural differences for HR that do make it harder, » Read more about: The potential of AI in human resource management »