TEMPORAL EVENTS ANALYSIS EMPLOYING TREE INDUCTION

摘要

An events analysis method comprises: optimizing respective to a set of training data a set of branching transition likelihood parameters associating parent events of type k with child events of type k′ in branching processes; inferring a most probable branching process for a set of input data comprising events based on the optimized set of branching transition likelihood parameters; and identifying rare or unusual events of the set of input data based on the inferred most probable branching process. An events analysis apparatus includes a probabilistic branching process learning engine configured to optimize the set of branching transition likelihood parameters, and a probabilistic branching process inference engine configured to infer the most probable branching process.