A probabilistic model for retrospective news event detection

A probabilistic model for retrospective news event detection is a 2005 paper that I still consider very valid. The problem faced is to detect when an event happened in the past. This can be very useful for building a chronicle service. The model prosed is a probabilistic model which incorporates both content and time information in a unified framework. Model parameters are estimated using Maximum Likelihood, where each article is charaterized by four indipendent probabilities. Namely, time, person, location and keywords. ML is extimated by using the classifical EM algorithm. Test are run on the TDT dataset.