Neural networks as essential parts of deep learning systems. The future? Technologies based on neural networks to allow greater exactness of predictive capacity.
Neural networks are a branch of machine learning born in the fifties but which only got established in recent years. An innovative and “disruptive” technology, with the advantage of continuously learning from data, guaranteeing ever higher performance.
How does it work?
Automatic learning algorithms use statistics and mathematics to find meaning (patterns), correlations and trends in huge amounts of data.
The more data they process, the more predictive capabilities they acquire. The machines are implementing increasingly accurate content reading and classification systems.
In Arca24 we are applying neural network systems and NLP (Natural Language Processing) text algorithms to CV screening in order to identify sections, images, keywords, date ranges and everything that can be useful to implement our semantic engine.
Thanks to new developments, the format requested from candidates during the registration phase will no longer be limited to reading files (eg doc, docx, pdf); the system will also be able to process the images. This will entail a considerable reduction in the fields to be filled in – much more information will be recovered when reading the CV – thus guaranteeing a better UX for the candidate.