About our AI and
Blockchain Platform

Personalization systems such as recommendation engines in recent years attracted the interest of many researchers and practitioners. Since Resnick and Varian first established the term “recommender system” in 1997, technologist have been improving recommendation quality and scalability of such systems by various means. While some programmers merged content-based with collaborative filtering in order to overcome sparsity problems and combine the advantages of both approaches, others focused on how to reduce the dimensionality of the user-item-matrix underlying collaborative filtering approaches.

Therefore, we built an AI solution into our platform that has answered the question: How can the connection of unique individuals in a niche social network of consumers and business professionals, be improved with AI in order to better match them together? To solve this using artificial intelligence, we used a polynomial (an expression consisting of variables and coefficients), that we created using a mathematical formula that fits data points together using a similar formula to Curve Fitting (https://en.wikipedia.org/wiki/Curve_fitting).