1. A computer-implemented method, comprising: obtaining, at a server having one or more processors, a training corpus including pairs of (i) documents and (ii) abstracts, each abstract representing a summary of a corresponding document; obtaining, at the server, part-of-speech (POS) tags and dependency parses for each abstract and each corresponding document; identifying, at the server, a set of entity mentions in each abstract and each corresponding document based on their respective POS tags and dependency parses; clustering, at the server, the sets of entity mentions referring to a same underlying entity to obtain clusters for each document and each corresponding abstract; aligning, at the server, specific abstract entity mentions to corresponding document entity mentions to obtain a set of aligned abstract and document entities; labeling, at the server, the set of aligned entities as salient and unaligned entities as non-salient to generate a labeled corpus; training, at the server, features of a classifier using the labeled corpus to obtain a trained classifier and generating, at the server, a model including the trained classifier, wherein the features include count features indicative of at least one of entity mentions and entity head word mentions, and wherein the training and generating further comprises bucketing, by the server, the count features by applying a function to the count features, wherein the function is: 
 ƒ( x )=round(log( k ( x+ 1))), where x represents a particular count feature and k controls the number of buckets; applying, at the server, the model to a collection of documents to obtain the salience estimates, the collection of documents representing a web browsing history of a user of a computing device; utilizing, at the server, the salience estimates to obtain a prediction of an advertisement that should be displayed to the user; and outputting, from the server and to the computing device via a network, the prediction, wherein receipt of the prediction causes the computing device to display the advertisement to the user.