Job offers recommender system based on virtual organizations

Human interaction has changed considerably with the emergence of the Internet. Today, a large percentage of daily communication takes place on instant messaging applications and social networks. In fact, there has been a considerable increase in the use of social networks because new social networks are being created for specific purposes, such as the search for employment or tourism. When the amount of content on a social network is large, it is necessary to help users find content of their interest. In this regard, artificial intelligence techniques can greatly facilitate the task of searching for relevant content. This paper presents a recommender system for a business and employment oriented social network, on which users are recommended job offers and other user profiles to follow. The presented system is based on virtual organizations of agents, and uses artificial neural networks to determine whether job offers and users should be recommended or not. The system has been evaluated on a real social network; its recommendations regarding job offers and user profiles have had a high acceptance rate.