Computer readable electronic records automated classification system
AssigneeEMC Corporation
InventorsThomas A. Summerlin, Timothy Shinkle, Russell E. Stalters
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Abstract
Classifying an electronic document in a computer-based system is disclosed. For each classification instance in a plurality of classification instances, a confidence data indicating a degree of confidence that the electronic document is associated with that classification instance is determined. A classification, based on a first classification instance in the plurality of classification instances, is assigned without human intervention to the electronic document if the confidence data associated with the first classification instance exceeds a first threshold.
Claims15
A method for classifying an electronic document in a computer-based system, comprising:
- generating a set of confidence data comprising for each of at least a subset of classification instances in a plurality of classification instances a corresponding determined confidence data, wherein a confidence data indicates a degree of confidence that the electronic document is associated with a corresponding classification instance;
- in the event at least one of the confidence data in the set exceeds a first predetermined threshold, assigning a classification to the electronic document without user input;
- and
- in the event none of the confidence data in the set exceeds the first predetermined threshold and that at least one of the confidence data in the set exceeds a second predetermined threshold that is lower than the first predetermined threshold, receiving user input and determining, based at least in part on the user input, which, if any, classification should be assigned to the electronic document.
A system for classifying an electronic document, comprising:
- a processor;
- and
- a memory coupled with the processor, wherein the memory is configured to provide the processor with instructions which when executed cause the processor to:
- generate a set of confidence data comprising for each of at least a subset of classification instances in a plurality of classification instances a corresponding determined confidence data, wherein a confidence data indicates a degree of confidence that the electronic document is associated with a corresponding classification instance;
- in the event at least one of the confidence data in the set exceeds a first predetermined threshold, assign a classification to the electronic document without user input;
- and
- in the event none of the confidence data in the set exceeds the first predetermined threshold and that at least one of the confidence data in the set exceeds a second predetermined threshold that is lower than the first predetermined threshold, receive user input and determining, based at least in part on the user input, which, if any, classification should be assigned to the electronic document.
A computer program product for classifying an electronic document, the computer program product being embodied in a non-transitory computer readable storage medium and comprising computer instructions for:
- generating a set of confidence data comprising for each of at least a subset of classification instances in a plurality of classification instances a corresponding determined confidence data, wherein a confidence data indicates a degree of confidence that the electronic document is associated with a corresponding classification instance;
- in the event at least one of the confidence data in the set exceeds a first predetermined threshold, assigning a classification to the electronic document without user input;
- and
- in the event none of the confidence data in the set exceeds the first predetermined threshold and that at least one of the confidence data in the set exceeds a second predetermined threshold that is lower than the first predetermined threshold, receiving user input and determining, based at least in part on the user input, which, if any, classification should be assigned to the electronic document.
Dependencies are inferred from the claim text.