MINING TEMPORAL PATTERNS IN LONGITUDINAL EVENT DATA USING DISCRETE EVENT MATRICES AND SPARSE CODING

摘要

Methods and systems for event pattern mining are shown that include representing longitudinal event data in a measurable geometric space as a temporal event matrix representation (TEMR) using spatial temporal shapes, wherein event data is organized into hierarchical categories of event type and performing temporal event pattern mining with a processor by locating visual event patterns among the spatial temporal shapes of said TEMR using a constraint sparse coding framework.