1. A vehicle information processing system for using a Bayesian network model to provide a probabilistically appropriate recommendation of media content to a recipient who receives the recommendation, the recipient being an occupant, the vehicle information processing apparatus comprising: a model storage unit storing a plurality of different Bayesian network models corresponding to a plurality of recipients, the Bayesian network models providing probabilistically appropriate recommendations of media content to the recipients based on recommendation conditions; a model selecting unit for selecting a first Bayesian network model from the stored Bayesian network models based on a recommendation condition associated with the recipient; a reasoning unit for reading the first Bayesian network model from the model storage unit, and for obtaining a recommendation of media content using probabilistic reasoning associated with the first Bayesian network model; a recommendation unit for providing the recommendation of media content to the recipient; a response receiving unit for receiving a response from the recipient in response to the recommendation of media content; a learning model information storage unit storing information associating learning models with corresponding Bayesian network models of the stored Bayesian network models; and a model learning unit for: identifying learning models associated with the first Bayesian network model based on the stored learning model information; learning the identified learning models based on the received response; and updating the identified learning models by specializing the identified learning models for the recommendation condition associated with the recipient, wherein the identified learning models include at least the first Bayesian network model and a second Bayesian network model, different from the first Bayesian network model, influenced by a result of the probabilistic reasoning associated with the first Bayesian network model.