14. The method of claim 9 , wherein estimating the parameters further comprises modeling time with a mixture model that is different than respective mixture models used to model document content associated with an event.
9. A computer-implemented method implemented using instructions stored on a computer-readable medium and executable by a computing device, the method comprising: initializing event parameters to identify a salient number of events from a corpus of documents, wherein the events comprise occurrences that are described in the corpus of documents, each event having an immediately preceding event in time and an immediately succeeding event in time, wherein the salient events are identified based on a salient score calculated by the amount of time between the immediately preceding event and the immediately succeeding event for each respective event; estimating parameters for a generative model for probabilistic retrospective detection of the events from the salient number of events, the generative model comprising respective models for person(s), time(s), location(s), and keyword(s); clustering events represented by documents using the parameters for the generative model; increasing or decreasing a number of events associated with respective ones of clustered events to re-initialize events; for respective event clusters, if a minimum or maximum number of events has not been reached, again performing operations of the estimating, clustering, and increasing or decreasing; and for respective event clusters, if a minimum or maximum number of events has been reached, summarizing events in resulting event clusters.