Adaptive Automata in Recommendation Systems

The recommendation systems look for to offer customized products to their users. These systems identify the users preferences and the preferences of the rest of the community to the products available. This article presents a recommendation system that uses an adaptive automaton to store the relationship between resources and the users´ preferences and determine the possible recommendations customized to each of its users. The details of the implementation are presented and discussed. An experiment is presented for verification and analysis of the recommendations generated in the developed system.