1. A method for training document similarity models, the method comprising: obtaining a set of training samples; obtaining prior information of document relations and non-relations for the set of training samples, wherein the prior information of document relations comprises information indicating that two or more documents in the set of training samples are considered related to each other, and wherein the prior information of document non-relations comprises information indicating that two or more documents in the set of training samples are not considered related to each other; and discriminatively training an ensemble of document similarity classification models using the set of training samples and using the prior information of document relations and non-relations using a processor of a computer, wherein the ensemble of document similarity classification models are discriminatively trained based at least in part on prior information of non-relation between a first document and a second document in the set of training samples such that a first classification model configured to determine document similarity with respect to the first document does not compete with a second classification model configured to determine document similarity with respect to the second document.