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Abstract

A system and a method for contextual categorization of data comprises a server having a processor and a non-transitory computer-readable storage medium in electronic communication with the processor and comprising program instructions executable by the processor to access an initial inventory of data set and metadata associated with the initial inventory of data set. The system is then configured to classify the initial inventory of data set by using the metadata into (a) reduced set of data comprising high level sensitivity classification and (b) a remainder data set. The system and method can be further configured for contextual categorization of data that involves receiving an initial data set to be categorized; establishing a library of contextual classifiers, the library comprising (1) a set of predetermined high level sensitivity classifications and (2) a set of user-generated business-specific sensitivity classifications subordinated below the high level sensitivity classifications; identifying and removing redundant, outdated, trivial or abandoned (ROTA) data from the initial data set to create a reduced data set and a remainder data set of ROTA data; applying the user-generated business-specific sensitivity classifications to the reduced data set to create a first set of classified data and a second set of unclassified data; and iteratively applying additional user-generated business-specific sensitivity classifications to the both the first set of classified data and the second set of unclassified data until all data in the reduced data set has been classified in exactly one use-generated business-specific sensitivity classification.

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First Claim