7. The method of claim 1 , wherein selecting, from the candidate documents D, a set S of quantity k of the candidate documents D based on a weighted-coverage function ƒ for the set T of query terms comprises: initializing an empty set of documents as the set S; and iteratively, until the set S includes the quantity k of the candidate documents D: selecting a document d, from the candidate documents D, that exhibits a maximum marginal increase in the weighted-coverage function ƒ, and that is not already in the set S, and adding the document d to the set S.
1. A computer-implemented method comprising: identifying, with one or more processors, a set T of query terms; selecting, with the one or more processors, candidate documents D that each satisfy one or more of the terms of the set T; selecting, from the candidate documents D, a set S of quantity k of the candidate documents D based on a weighted-coverage function ƒ for the set T of terms; pairing each document in the set S with another document in the set S based on a distance between the paired documents; generating, with the one or more processors, a set C of clusters from the paired documents, each cluster in the set C being associated with one or more topics of the query terms; selecting, with the one or more processors, from the set S, a set V of quantity p documents, for one or more clusters of the set C, based on a diversity function, wherein the diversity function is expressed as (Σ 1≦i≦k, 1≦j≦p Σ 1≦i′≦k′, 1≦j′≦p GJD(D i j , D i′ j′ )); and providing for presentation the set V of documents as representative documents that cover one or more topics associated with the one or more clusters.