METHOD AND SYSTEM FOR USING MACHINE LEARNING TECHNIQUES TO MAKE HIGHLY RELEVANT AND DE-DUPLICATED OFFER RECOMMENDATIONS

Patent №

US 10,706,453

Granted

2020-07-07

Filed 2018

Owner

INTUIT INC.

Lab

AI components

4

ml · kr · planning · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

15866005

Big data analysis methods and machine learning based models are used to provide offer recommendations to consumers that are probabilistically determined to be relevant to a given consumer. Machine learning based matching of user attributes and offer attributes is first performed to identify potentially relevant offers for a given consumer. A de-duplication process is then used to identify and eliminate any offers represented in the offer data that the consumer has already seen, has historically shown no interest in, has already accepted, that are directed to product or service types the user/consumer already owns, for which the user does not qualify, or that are otherwise deemed to be irrelevant to the consumer.

Machine learningKnowledge representationPlanningAI hardwareG06Q 30/0631G06N 3/09G06N 5/01G06N 20/00G06N 20/20G06N 3/08G06N 20/10

AI classification

Machine learning1.00
Planning1.00
AI hardware1.00
Knowledge representation0.95
Vision0.49
Natural language0.29
Evolutionary computation0.02
Speech0.00

Ownership

INTUIT INC.

assignment · 445760299

Assignors

MORIN, YAO H., JENNINGS, JAMES, RODRIGUEZ, CHRISTIAN A., PEI, LEI, RAITURKAR, JYOTISWARUP PAI

On an employer assignment, the assignors are typically the inventors.

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