Automatic labeling of social network users Scientia.Net through the machine learning supervised application

This work evaluates clustering techniques and pattern classification and proposes a model that uses a combination of supervised learning algorithms and unsupervised learning ones with the goal of creating groups and identifying which attributes can define them (labeling) applied to social network called Scientia.Net. The tests were done using a database with around 2000 users. The proposed model shows the results applied to the database Scientia.Net.