This area includes the distributed diagnosis and classification, large-scale semantic search, social networking analysis, and analysis of emotions and feelings.
Early research on machine learning in artificial systems date back to the 1950's. From the 80 start to develop practical applications of algorithms called "subsymbolic"(mainly Bayesian neural networks and systems) to problems of pattern recognitionand classification and the "symbolic" (induction of trees and rules) to knowledge acquisition for expert systems. In the 90 off with force what has been called 'data mining' application of learning algorithms and visualization for knowledge extractionin large databases. Our contributions in this field have also followed this path: