11. A system comprising: a data store storing images; and one or more computers that interact with the data store and execute instructions that cause the one more computers to perform operations comprising: obtaining text associated with an image; obtaining a feature vector representing visual features of the image; parsing the text into candidate labels for the image, each candidate label being a unique n-gram of the text; determining that an image classification model has been trained for an n-gram matching one or more of the candidate labels, wherein the image classification model has been trained to classify images based on the feature vector; and assigning at least one of the one or more candidate labels as a label for the image based on the feature vector and the image classification model for the n-gram matching the one or more candidate labels.
11. A system comprising: a data store storing images; and one or more computers that interact with the data store and execute instructions that cause the one more computers to perform operations comprising: obtaining text associated with an image; obtaining a feature vector representing visual features of the image; parsing the text into candidate labels for the image, each candidate label being a unique n-gram of the text; determining that an image classification model has been trained for an n-gram matching one or more of the candidate labels, wherein the image classification model has been trained to classify images based on the feature vector; and assigning at least one of the one or more candidate labels as a label for the image based on the feature vector and the image classification model for the n-gram matching the one or more candidate labels. 12. The system of claim 11 , wherein the instructions cause the one or more computers to perform operations comprising: computing a classification score for the image to the one or more candidate labels based on the feature vector and the image classification model for the n-gram matching the one or more candidate labels; and classifying the image as relevant to the one or more candidate labels based on the classification score.