1. A system for cross-media recommendation, comprising: a first database operable to store a plurality of taste profiles corresponding to a first domain; a second database operable to store a plurality of media item vectors corresponding to a second domain; and at least one processor configured to: generate a training set based on the plurality of taste profiles and the plurality of media item vectors; apply an evaluation taste profile in the first domain to a plurality of models generated based on a relationship among the plurality of taste profiles and the plurality of media item vectors, wherein the plurality of models are trained based on the training set; obtain a plurality of resulting codes corresponding to at least one of the plurality of media item vectors in the second domain; generate a plurality of weighted term vectors based on the plurality of taste profiles; generate vector quantized media data by vector quantizing the plurality of media item vectors; and generate a map of the weighted term vectors to the vector quantized media data, wherein the plurality of weighted term vectors are generated by multiplying, for each term in a taste profile, an affinity by a probability that the term is associated with a media item.