Machine-assisted publisher classification
First Claim
1. A computer-implemented method for classifying content publishers, comprising:
- receiving data associated with a plurality of classified content publishers, the data including training data and testing data;
training a classifier model using at least a portion of the training data;
defining a first category of the classifier model, the first category identifying allowable content publishers;
defining a second category of the classifier model, the second category identifying disallowable content publishers;
defining a third category of the classifier model, the third category identifying content publishers needing further review;
testing the classifier model using at least a portion of the testing data;
determining that a precision level associated with the classifier model has at least met a specified precision threshold;
receiving data associated with an unclassified content publisher;
calculating a score for the unclassified content publisher based at least in part on processing the data associated with the unclassified content publisher using the classifier model; and
classifying the unclassified content publisher as belonging to one of the first category, the second category, or the third category, the classifying being based upon the score for the unclassified content publisher.
1 Assignment
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Accused Products
Abstract
One or more computing systems can implement a classifier to classify content publishers as being likely to provide appropriate content or as being likely to provide inappropriate content. The classifier can gather information from previously classified publishers. The information from the previously classified publishers can used to train the classifier. Based on the training, the classifier can learn about traits, characteristics, and/or behavioral patterns, etc., associated with publishers that have been previously classified as being good as well as publishers previously classified as being bad. The classifier can then process information about an unclassified publisher to determine a classification for the unclassified publisher, as being good (and likely to provide appropriate content) or bad (and likely to provide inappropriate content).
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Citations
25 Claims
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1. A computer-implemented method for classifying content publishers, comprising:
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receiving data associated with a plurality of classified content publishers, the data including training data and testing data; training a classifier model using at least a portion of the training data; defining a first category of the classifier model, the first category identifying allowable content publishers; defining a second category of the classifier model, the second category identifying disallowable content publishers; defining a third category of the classifier model, the third category identifying content publishers needing further review; testing the classifier model using at least a portion of the testing data; determining that a precision level associated with the classifier model has at least met a specified precision threshold; receiving data associated with an unclassified content publisher; calculating a score for the unclassified content publisher based at least in part on processing the data associated with the unclassified content publisher using the classifier model; and classifying the unclassified content publisher as belonging to one of the first category, the second category, or the third category, the classifying being based upon the score for the unclassified content publisher. - View Dependent Claims (2, 3, 4)
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5. A computer-implemented method comprising:
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receiving information about one or more classified publishers; modifying a classifier model based at least in part on the information about the one or more classified publishers; defining a first category of the classifier model, the first category identifying allowable content publishers; defining a second category of the classifier model, the second category identifying disallowable content publishers; defining a third category of the classifier model, the third category identifying content publishers needing further review; determining that a quality level associated with the classifier model at least meets a specified quality threshold; receiving information about at least one publisher, the at least one publisher being unclassified; processing at least a portion of the information about the at least one publisher using the modified classifier model; and classifying each of the at least one publisher as belonging to one of the first category, the second category or the third category, based at least in part on the processing at least the portion of the information by the modified classifier model. - View Dependent Claims (6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18)
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19. A system comprising:
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a processor; and a memory device including instructions that, when executed by the processor, cause the system to; receive information about one or more classified publishers; modify a classifier model based at least in part on the information about the one or more classified publishers; define a first category of the classifier model, the first category identifying allowable content providers; define a second category of the classifier model, the second category identifying disallowable content providers; define a third category of the classifier model, the third category identifying content publishers needing further review; determine that a quality level associated with the classifier model at least meets a specified quality threshold; receive information about at least one publisher, the at least one publisher being unclassified; process at least a portion of the information about the at least one publisher using the modified classifier model; and classify each of the at least one publisher as belonging to one of the first category, the second category or the third category, based at least in part on the processing at least the portion of the information by the modified classifier model. - View Dependent Claims (20, 21, 22, 23)
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24. A non-transitory computer-readable storage medium including instructions for identifying elements, the instructions when executed by a processor of a computing system causing the computing system to:
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receive information about one or more classified publishers; modify a classifier model based at least in part on the information about the one or more classified publishers; define a first category of the classifier model for allowable content publishers; define a second category of the classifier model for disallowable content providers; define a third category of the classifier model, the third category identifying content publishers needing further review; determine that a quality level associated with the classifier model at least meets a specified quality threshold; receive information about at least one publisher, the at least one publisher being unclassified; process at least a portion of the information about the at least one publisher using the modified classifier model; and classify each of the at least one publisher as belonging to one of the first category, the second category, or the third category, based at least in part on the processing at least the portion of the information by the modified classifier model. - View Dependent Claims (25)
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Specification