1. A computer-implemented method comprising: aggregating news documents from one or more news sources; grouping the news documents into a plurality of news collections, each of the plurality of news collections including a sub-set of the news documents having related content; determining objects described by the plurality of news collections, the objects collectively forming a set of objects; determining an overall relevance of each of the plurality of news collections by determining a number of news sources in each of the plurality of news collections reporting on a related topic; determining a level of interest in the objects described by the plurality of news collections by determining a number of other news collections mentioning the objects and a number of search queries searching for information about the objects during a predetermined timeframe; determining a significance of the objects in the plurality of news collections by determining a number of times that the objects appear in titles of the news documents of the plurality of news collections, a centrality of the objects in the news documents of the plurality of news collections, the centrality of the objects being based on where the objects are mentioned in a body of the news documents, and a pertinence of events described by the plurality of news collections involving the objects; determining a relevance of each of the plurality of news collections with respect to the objects respectively described by the plurality of news collections, the relevance being based on the overall relevance of each of the plurality of news collections, the level of interest in the objects described by the plurality of news collections, and the significance of the objects in the plurality of news collections; and determining one or more news collections from the plurality of news collections to be associated with a first object included in the set of objects based on the relevance of the one or more news collections to the first object.