Abstract: In described embodiments, fluid user models are employed for personalized mobile applications, referred to herein as recommender systems. The described embodiments augment media with additional information highly personalized to a user based on a variety of factors with different time sensitivity and include, but are not limited to, a user's general preferences, history, immediate context and attention, and emotional states when the user experiences and/or interacts with the media. Embodiments solve various problems of information overload stemming from both i) the complexity in characterizing the information and ii) its potential relevancy and in understanding and coding the user's needs.