US 12,293,375 B2
Technologies for using machine learning to determine product certification eligibility
Scot Webster, Northbrook, IL (US); Mahmood Tabaddor, Rochester, MI (US); John C. Jones, Gilberts, IL (US); and Mario Xerri, Melville, NY (US)
Assigned to UL LLC, Northbrook, IL (US)
Filed by UL LLC, Northbrook, IL (US)
Filed on Oct. 30, 2020, as Appl. No. 17/084,701.
Claims priority of provisional application 62/933,175, filed on Nov. 8, 2019.
Prior Publication US 2021/0142334 A1, May 13, 2021
Int. Cl. G06Q 30/018 (2023.01); G06N 20/00 (2019.01)
CPC G06Q 30/018 (2013.01) [G06N 20/00 (2019.01)] 5 Claims
OG exemplary drawing
 
1. A computer-implemented method of using machine learning to determine product certification eligibility, the method comprising:
training, by a computer processor, a plurality of machine learning models using a set of training data associated with a set of appliances, the set of training data comprising (i) textual and visual content corresponding to the set of appliances, wherein the visual content comprises, for each appliance of the set of appliances, a training schematic drawing depicting appliance wiring of that appliance, and wherein the training schematic drawing comprises a label for a category of a plurality of categories;
storing the plurality of machine learning models in a memory;
accessing, by the computer processor, a specification (i) comprising a schematic depicting an appliance wiring of an appliance, (ii) identifying a certification, and (iii) indicating a geographic area or jurisdiction corresponding to an envisioned market for the appliance, wherein the certification is applicable to the geographic area or jurisdiction;
performing, by the computer processor, a visual analysis technique on the schematic to determine a set of components, a set of materials, and a length for the appliance wiring;
identifying, by the computer processor, a machine learning model of the plurality of machine learning models that corresponds to (i) the appliance, and (ii) the geographic area or jurisdiction corresponding to the envisioned market for the appliance;
analyzing, by the computer processor using the machine learning model, the specification, including the set of components, the set of materials, and the length for the appliance wiring to:
determine a set of keywords associated with the appliance, wherein each keyword of the set of keywords has a type that is one of an ineligible keyword, a trigger keyword, or an eligible keyword, and
output an indication that the appliance is ineligible for the certification, wherein the indication is based at least on the type of each keyword of the set of keywords;
determining a set of changes that need to be implemented in the appliance that would result in the appliance being eligible for the certification;
automatically performing, by the computer processor without user intervention, a review to reconcile or clarify any of the set of keywords being the trigger keyword type; and
determining, by the computer processor, a reason when none of the set of keywords is the eligible keyword type.