  In events that are composed by many activities, there is a problem that
involves retrieve and management the information of visitors that are visiting
the activities. This management is crucial to find some activities that are
drawing attention of visitors; identify an ideal positioning for activities;
which path is more frequented by visitors. In this work, these features are
studied using Complex Network theory. For the beginning, an artificial database
was generated to study the mentioned features. Secondly, this work shows a
method to optimize the event structure that is better than a random method and
a recommendation system that achieves ~95% of accuracy.
