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METHODS AND SYSTEMS FOR CLASSIFYING DATABASE RECORDS BY INTRODUCING TIME DEPENDENCY INTO TIME-HOMOGENEOUS PROBABILITY MODELS

Abstract:

Methods and systems are described herein for improving data processing efficiency of classifying user files in a database. More particularly, methods and systems are described herein for improving data processing efficiency of classifying user files in a database in which the user files have a temporal element. The methods and system described herein accomplish these improvements by introducing time dependency into time-homogeneous probability models. Once time dependency has been introduced into the time-homogeneous probability models, these models may be used to improve the data processing efficiency of classifying the user files that feature a temporal element.