Enhancing training of predictive coding systems through user selected text
First Claim
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1. A method comprising:
- updating, by a predictive coding system, a set of training documents based on a selected portion of a training document of the set to obtain an updated set of training documents;
searching, by the predictive coding system, content within other training documents in the updated set using a machine learning engine based on the selected portion and variations of the selected portion;
determining a probability measure for the content; and
classifying, by the predictive coding system, a second training document containing the content based on the probability measure.
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Abstract
An exemplary predictive coding system can be programmed to update a plurality of training documents based on a portion of a training document selected by a user. The predictive coding system generates a machine learning engine based on the updated plurality of training documents. The predictive coding system predicts a classification for one or more remaining documents from the plurality of training documents using the machine learning engine.
27 Citations
18 Claims
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1. A method comprising:
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updating, by a predictive coding system, a set of training documents based on a selected portion of a training document of the set to obtain an updated set of training documents; searching, by the predictive coding system, content within other training documents in the updated set using a machine learning engine based on the selected portion and variations of the selected portion; determining a probability measure for the content; and classifying, by the predictive coding system, a second training document containing the content based on the probability measure. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A non-transitory computer readable storage medium having instructions that, when executed by a processing device, cause the processing device to perform operations comprising:
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updating a set of training documents based on a selected portion of a training document of the set to obtain an updated set of training documents; searching content within other training documents in the updated set using a machine learning engine based on the selected portion and variations of the selected portion; determining a probability measure of the content; and classifying a second training document containing the content based on the probability measure. - View Dependent Claims (8, 9, 10, 11, 12)
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13. A system comprising:
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a memory; and a processing device coupled to the memory, wherein the processing device is configured to; update a set of training documents based on a selected portion of a training document of the set to obtain an updated set of training documents; search content within other training documents in the updated set using a machine learning engine based on the selected portion and variations of the selected portion; and determine a probability measure of the content; and classify a second training document containing the content based on the probability measure. - View Dependent Claims (14, 15, 16, 17, 18)
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Specification