IP Library Granted Patent US 10,803,105
Granted Patent B1
US 10,803,105 · App. 16/704,046 · Granted Oct 13, 2020

Computer-implemented method for performing hierarchical classification

Inventors: George Beskales (Waltham, MA); John Kraemer (Somerville, MA); Ihab F. Ilyas (Waterloo, CA); Liam Cleary (Dublin, IE); Paul Roome (Oakland, CA)
Assignee: Tamr, Inc.
G06F16/353G06K9/6282G06N20/00
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Quick Facts
Patent No.
US 10,803,105
App. No.
16/704,046
Granted
Oct 13, 2020
Kind
B1
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.

Claims (11)

1. 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) consolidating, by the software, the unlabeled records through deduplication or clustering;

(d) identifying, by the software, a subset of the hierarchical classes as being candidate hierarchical classes for each of the unlabeled records;

(e) predicting, by the software, hierarchical classifications for each record in the unlabeled records using the plurality of binary classifiers;

(f) scoring, by the software, using a scoring function, each of the predicted hierarchical classifications of the unlabeled records;

(g) obtaining, by the software, using a search algorithm, a top-scoring predicted hierarchical classification of each unlabeled record; and

(h) outputting, by the software, the top-scoring predicted hierarchical classification as the predicted classification for each of the unlabeled records,

wherein steps (e)-(h) are performed on the consolidated records, and

wherein the hierarchical classifications for each record in the unlabeled records are predicted, by the software, using only the candidate hierarchical classes for each of the unlabeled records.

Assignments (6)
RELEASE OF SECURITY INTEREST Recorded Feb 21, 2025
From: JPMORGAN CHASE BANK, N.A.
To: TAMR, INC.
Reel/Frame 070284/0092 →
RELEASE OF SECURITY INTEREST Recorded Feb 21, 2025
From: JPMORGAN CHASE BANK, N.A.
To: TAMR, INC.
Reel/Frame 070284/0101 →
AMENDED AND RESTATED INTELLECTUAL PROPERTY SECURITY AGREEMENT Recorded Jan 30, 2023
From: TAMR, INC.
To: JPMORGAN CHASE BANK, N.A.
Reel/Frame 062540/0438 →
INTELLECTUAL PROPERTY SECURITY AGREEMENT Recorded Mar 19, 2021
From: TAMR, INC.
To: JPMORGAN CHASE BANK, N.A.
Reel/Frame 055662/0240 →
INTELLECTUAL PROPERTY SECURITY AGREEMENT Recorded Dec 17, 2020
From: TAMR, INC.
To: WESTERN ALLIANCE BANK
Reel/Frame 055205/0909 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 12, 2019
From: BESKALES, GEORGE; KRAEMER, JOHN; ILYAS, IHAB F.; CLEARY, LIAM; ROOME, PAUL
To: TAMR, INC.
Reel/Frame 051266/0763 →
Continuity (2)
Continuation 15836188 · Dec 8, 2017
Provisional Application 62540804 · Aug 3, 2017
Cited By (2)
US 12,242,982 US 12,561,620