1. A method performed by one or more server devices, comprising: storing, in a memory associated with the one or more server devices, feature data associated with features of links within documents where the feature data specifies one or more values for at least some of the features, and where the features are independent of user behavior; generating, by the one or more server devices, feature vectors for the links based on the stored feature data; storing, in a memory associated with the one or more server devices, user data relating to the links, where the user data includes user class data and user behavior data; generating, using one or more processors of the one or more server devices, a model that identifies a probability that a particular link, associated with one or more particular features, will be selected by a particular user, associated with one or more user classes or behaviors, where generating the model includes: analyzing the generated feature vectors and the stored user data in relation to selections of links made by users while viewing a document that includes one of the links, and in relation to the one or more user classes or behaviors; and analyzing the generated feature vectors and the stored user data in relation to users viewing a document that includes one of the links and not selecting the one of the links, and in relation to the one or more user classes or behaviors; storing, in a memory associated with the one or more server devices, the model; and calculating, by at least one of the one or more server devices and based on the generated model, a probability that the particular link will be selected by the particular user.
1. A method performed by one or more server devices, comprising: storing, in a memory associated with the one or more server devices, feature data associated with features of links within documents where the feature data specifies one or more values for at least some of the features, and where the features are independent of user behavior; generating, by the one or more server devices, feature vectors for the links based on the stored feature data; storing, in a memory associated with the one or more server devices, user data relating to the links, where the user data includes user class data and user behavior data; generating, using one or more processors of the one or more server devices, a model that identifies a probability that a particular link, associated with one or more particular features, will be selected by a particular user, associated with one or more user classes or behaviors, where generating the model includes: analyzing the generated feature vectors and the stored user data in relation to selections of links made by users while viewing a document that includes one of the links, and in relation to the one or more user classes or behaviors; and analyzing the generated feature vectors and the stored user data in relation to users viewing a document that includes one of the links and not selecting the one of the links, and in relation to the one or more user classes or behaviors; storing, in a memory associated with the one or more server devices, the model; and calculating, by at least one of the one or more server devices and based on the generated model, a probability that the particular link will be selected by the particular user. 6. The method of claim 1 , further comprising: assigning a weight to the particular link, where the weight reflects the probability that the link will be selected.