Recommender systems are very present in our daily life but go unnoticed: they help us decide which product we should buy, which hotel we should choose to go on holidays or which movie we should watch at weekends. You can learn more about them by Netflix recommender system here: http://www.theverge.com/2016/2/17/11030200/netflix-new-recommendation-system-global-regional.
ISOIN is researching these systems and learning their methods, algorithms and details of recommendations. Currently our team innovates on creative ideas and new ways to approach these systems. The ideas which we are working are mainly based on mathematical knowledge that we could apply into this new technology. In a curious way, we can perform many different techniques: from the equivalence relations (abstract algebra), classic geometry and planes, through artificial intelligence and machine learning. We are going to continue working on these interesting systems in order to get new useful techniques to make recommendations.