11. The method of claim 9 , further comprising: obtaining data identifying a training resource viewed by a user; obtaining data identifying an advertisement in a first resource selected by the user within a threshold time window of viewing the training resource; and associating a keyword used in placing the advertisement in the first resource with the training resource viewed by the user as a concept term.
9. A method for training a system for predicting a relevance of each of a set of pre-determined concept terms to resources, wherein the system includes an embedding function layer, one or more neural network layers, and a classifier, and wherein the method comprises: obtaining data identifying training resources and one or more respective associated concept terms for each of the training resources; specifying output criteria for a respective predicted output generated by the classifier for each of the training resources; and training the embedding function layer, the neural network layers, and the classifier based on respective features of each the training resources and on the specified output criteria, wherein each feature is a value of a respective attribute of the resource.