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US 11,232,143 B1Granted
Computer-implemented method for performing hierarchical classification
AssigneeTamr, Inc.
InventorsGeorge Beskales, John Kraemer, Ihab F. Ilyas, Liam Cleary, Paul Roome
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Abstract
Given a number of records and a number of target classes to which these records belong to, a (weakly) supervised machine learning classification method leverages known possibly dirty classification rules, efficiently and accurately learns a classification model from training data, and applies the learned model to the data records to predict their classes.
Claims3
A computer-implemented method for performing hierarchical classification comprising:
- (a) inputting, into software running on one or more computer processors, training data records having known classification labels and unlabeled records;
- (b) building, by the software, a classification model from the training data records that is configured to predict a hierarchical class of an unlabeled record, the classification model including a plurality of binary classifiers, each binary classifier being configured to predict whether an unlabeled record belongs to a certain hierarchical class;
- (c) predicting, by the software, hierarchical classifications for each record in the unlabeled records using the plurality of binary classifiers;
- (d) scoring, by the software, using a scoring function, each of the predicted hierarchical classifications of the unlabeled records;
- (e) obtaining, by the software, using a search algorithm, a top-scoring predicted hierarchical classification of each unlabeled record;
- and
- (f) outputting, by the software, the top-scoring predicted hierarchical classification as the predicted classification for each of the unlabeled records.
4 more elements
Dependencies are inferred from the claim text.