Technologies such as semantics, Machine Learning and Text Classification, allow you to conduct a logical analysis of texts, identifying semantic relationships and possible connections between words and extrapolating concepts.
Why using semantics?
Semantic technology defines and connects information by developing languages to express rich and self-descriptive interrelationships of data in a form that machines can process and store. In this way, the machine is not only able to process long strings of characters and contextualize them, but also allows you to store, manage and retrieve information based on meaning and logical relationships, and relate them to each other.
Applications in the HR world
The use of these technologies in recruiting processes allows specific information relating to professional experience and skills to be extracted and processed from the candidates’ CVs.
The result? A significant reduction in the processing time of candidates’ CVs, greater strategic value for the work of recruiters and optimization of the entire process of recruiting and selecting staff.
A dedicated team is working progressively with the aim of enhancing our semantic engine, thus ensuring a more accurate association between candidates and job advertisements. To date, our Semantic Analysis system is available in: Italian, English, French, German, Spanish, Portuguese, Polish, Catalan, Russian, Romanian, Dutch, Danish, Norwegian, Finnish, Greek, Turkish, Arabic and Chinese.