Invention Grant
- Patent Title: Inferring consumer affinities based on shopping behaviors with unsupervised machine learning models
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Application No.: US15140762Application Date: 2016-04-28
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Publication No.: US10417653B2Publication Date: 2019-09-17
- Inventor: Stephen Milton , Duncan McCall
- Applicant: PlaceIQ, Inc.
- Applicant Address: US NY New York
- Assignee: PlaceIQ, Inc.
- Current Assignee: PlaceIQ, Inc.
- Current Assignee Address: US NY New York
- Agency: Pillsbury Winthrop Shaw Pittman LLP
- Main IPC: G06F16/00
- IPC: G06F16/00 ; G06Q30/02 ; H04W4/029

Abstract:
A process of discovering psychographic segments of consumers with unsupervised machine learning. A first set of consumer-behavior is converted into respective consumer-behavior vectors for training an unsupervised machine learning model. The unsupervised machine learning model is trained with the first set of consumer-behavior vectors to determine psychographic segments of consumers. A second set of consumer-behavior records is obtained after determining the psychographic segments of consumers and the second set of consumer-behavior records is converted into respective consumer-behavior vectors. The second set of consumer-behavior vectors is classified as each belonging to at least a respective one of psychographic segments with the trained machine learning model to predict, based on the classification, a likelihood of the respective consumer engaging in behavior associated with a corresponding one of the psychographic segments.
Public/Granted literature
- US20160239857A1 INFERRING CONSUMER AFFINITIES BASED ON SHOPPING BEHAVIORS WITH UNSUPERVISED MACHINE LEARNING MODELS Public/Granted day:2016-08-18
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