公开(公告)号：US20210035183A1

公开(公告)日：2021-02-04

申请号：US16527130

申请日：2019-07-31

Applicant: Synchronoss Technologies, Inc.

Inventor： Casimir Saternos ,  Alec Lazarescu

IPC: G06Q30/06 ,  G06N20/20 ,  G06Q30/02

Abstract: A computer implemented method and system for a recommendation engine utilizing progressive labeling and user context enrichment. The method comprises receive a request from a current user of a user device, for a recommendation of an item, wherein the request comprises an image of the item; analyzing the item in the image using a plurality of objective machine learning models, wherein analyzing the item in the image comprises assigning an objective label and a percentage of confidence in the assigned label for each of the objective machine learning models; analyzing the item in the image using a plurality of subjective machine learning models wherein analyzing the item in the image comprises assigning an subjective label and a percentage of confidence in the assigned label for each of the subjective machine learning models; retrieving user context information for the current user; generating a plurality of new labels based on the objecting labels, subjective labels, and user context information, wherein each of the plurality of new labels includes a weight signifying the importance of each new label; retrieve one or more recommendations, wherein the one or more recommendations comprise universal resource locations to clothing that matches the labels assigned to the image; and transmit the one or more recommendations to the user device when a confidence level in the recommendations exceeds a predefined threshold.