Different economic actors, notably companies belonging to different market segments can meet on digital platforms in order to exchange. The development of this network can lead to the appearance of a Digital Business Ecosystem (DBE). However, the complexity of these exchanges, and the intensity of the flow of information exchanged can make it difficult for a company to find partners that meet its needs. In our research, we propose a method to identify the best customers, suppliers and other kinds of partners based on the intentions of users and the economic and business context of these companies. This recommendation system is based on matchmaking with supervised hybrid machine learning algorithms. The current work is part of the search for a more generic method of orchestrating these companies, called entities, within a Digital Business Ecosystem.