System and method for classifying data
First Claim
1. A method comprising:
- on a computer system comprising at least one server computer, providing a plurality of distinct data classification engines, wherein the plurality of distinct data classification engines comprising an a priori classification engine, a posteriori classification engine, and a heuristics engine;
wherein the a priori classification engine is operable to perform an a priori classification, the a priori classification comprising utilization of a set of user-specified classification rules;
wherein the a posteriori classification engine is operable to perform an a posteriori classification, the a posteriori classification comprises utilization of one or more probabilistic algorithms;
wherein the heuristics engine is operable to perform a heuristics classification, the heuristics classification comprising analysis of at least one of a number and a percentage of characteristics of particular data that match a profile of a particular classification;
accessing, by the computer system, the data from at least one source;
responsive to an indication that the a priori classification should be performed, performing, by the computer system via the priori classification engine, the a priori classification on the data to classify the data;
responsive to an indication that the a posteriori classification should be performed, performing, by the computer system via the a posteriori classification engine, the a posteriori classification on the data to classify the data;
verifying whether the previously classified data has been correctly classified;
responsive to a determination that the previously classified data has not been correctly classified, the posteriori classification reclassifies the previously classified data and updates the one or more probabilistic algorithms used for classifying the data; and
responsive to an indication that the heuristics classification should be performed, performing, by the computer system via the heuristics engine, the heuristics classification on the data to classify the data.
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Accused Products
Abstract
In one embodiment, a method includes providing an a priori classification engine, an a posteriori classification engine, and a heuristics engine. The a priori classification engine is operable to perform an a priori classification. The a posteriori classification engine is operable to perform an a posteriori classification. The heuristics engine is operable to perform a heuristics classification. In addition, the method includes accessing data from at least one source. The method further includes, responsive to an indication that the a priori classification should be performed, performing the a priori classification on the data. The method also includes, responsive to an indication that the a posteriori classification should be performed, performing the a posteriori classification on the data. Further, the method includes, responsive to an indication that the heuristics classification should be performed, performing the heuristics classification on the data.
330 Citations
20 Claims
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1. A method comprising:
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on a computer system comprising at least one server computer, providing a plurality of distinct data classification engines, wherein the plurality of distinct data classification engines comprising an a priori classification engine, a posteriori classification engine, and a heuristics engine; wherein the a priori classification engine is operable to perform an a priori classification, the a priori classification comprising utilization of a set of user-specified classification rules; wherein the a posteriori classification engine is operable to perform an a posteriori classification, the a posteriori classification comprises utilization of one or more probabilistic algorithms; wherein the heuristics engine is operable to perform a heuristics classification, the heuristics classification comprising analysis of at least one of a number and a percentage of characteristics of particular data that match a profile of a particular classification; accessing, by the computer system, the data from at least one source; responsive to an indication that the a priori classification should be performed, performing, by the computer system via the priori classification engine, the a priori classification on the data to classify the data; responsive to an indication that the a posteriori classification should be performed, performing, by the computer system via the a posteriori classification engine, the a posteriori classification on the data to classify the data; verifying whether the previously classified data has been correctly classified; responsive to a determination that the previously classified data has not been correctly classified, the posteriori classification reclassifies the previously classified data and updates the one or more probabilistic algorithms used for classifying the data; and responsive to an indication that the heuristics classification should be performed, performing, by the computer system via the heuristics engine, the heuristics classification on the data to classify the data. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. An information handling system comprising:
a processing unit, wherein the processing unit is operable to implement a method comprising; providing a plurality of distinct data classification engines, wherein the plurality of distinct data classification engines comprising an a priori classification engine, a posteriori classification engine, and a heuristics engine; wherein the a priori classification engine is operable to perform an a priori classification, the a priori classification comprising utilization of a set of user-specified classification rules; wherein the a posteriori classification engine is operable to perform an a posteriori classification, the a posteriori classification comprises utilization of one or more probabilistic algorithms; wherein the heuristics engine is operable to perform a heuristics classification, the heuristics classification comprising analysis of at least one of a number and a percentage of characteristics of particular data that match a profile of a particular classification; accessing data from at least one source; responsive to an indication that the a priori classification should be performed, performing, via the priori classification engine, the a priori classification on the data to classify the data; responsive to an indication that the a posteriori classification should be performed, performing, via the a posteriori classification engine, the a posteriori classification on the data to classify the data; verifying whether the previously classified data has been correctly classified; responsive to a determination that the previously classified data has not been correctly classified, the posteriori classification reclassifies the previously classified data and updates the one or more probabilistic algorithms used for classifying the data; and responsive to an indication that the heuristics classification should be performed, performing, via the heuristics engine, the heuristics classification on the data to classify the data. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19)
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20. A computer-program product comprising a non-transitory computer-usable medium having computer-readable program code embodied therein, the computer-readable program code adapted to be executed to implement a method comprising:
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providing a plurality of distinct data classification engines, wherein the plurality of distinct data classification engines comprising an a priori classification engine, a posteriori classification engine, and a heuristics engine; wherein the a priori classification engine is operable to perform an a priori classification, the a priori classification comprising utilization of a set of user-specified classification rules; wherein the a posteriori classification engine is operable to perform an a posteriori classification, the a posteriori classification comprises utilization of one or more probabilistic algorithms; wherein the heuristics engine is operable to perform a heuristics classification, the heuristics classification comprising analysis of at least one of a number and a percentage of characteristics of particular data that match a profile of a particular classification; accessing data from at least one source; responsive to an indication that the a priori classification should be performed, performing, via the priori classification engine, the a priori classification on the data to classify the data; responsive to an indication that the a posteriori classification should be performed, performing, via the a posteriori classification engine, the a posteriori classification on the data to classify the data; verifying whether the previously classified data has been correctly classified; responsive to a determination that the previously classified data has not been correctly classified, the posteriori classification reclassifies the previously classified data and updates the one or more probabilistic algorithms used for classifying the data; and responsive to an indication that the heuristics classification should be performed, performing, via the heuristics engine, the heuristics classification on the data to classify the data.
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Specification