METHOD AND SYSTEM FOR GENERATING DIGITAL TASK LABEL BY MACHINE LEARNING ALGORITHM Russian patent published in 2024 - IPC G06N20/00 

FIELD: physics.

SUBSTANCE: invention relates to a method and a system for generating a digital task label using a machine learning algorithm (MLA). Method is performed by a server connected to the crowdsourced digital platform and includes: at the training stage: receiving by the server a digital training task for execution on the crowdsourced digital platform; receiving, by a server, a plurality of digital training task labels corresponding to the digital training task from a plurality of client devices associated with workers, wherein said plurality of client devices is associated with a crowdsourced digital platform, in response to the digital training task sent to the plurality of client devices using the crowdsourced digital platform; receiving, by the server, a digital mark history containing the digital task marks previously received from each client device; training by the server of the MLA algorithm, which includes: input by the server of the digital training task into the MLA algorithm capable of generating a vector representation of the task corresponding to the vector representation of the digital training task; input by the server of digital labels histories into the MLA algorithm to form a vector representation of the employee with which the given client device is connected from the plurality of client devices; wherein the formation of a vector representation of an employee with which said client device is connected includes: determining for a given worker, with which a given client device is connected, a latent parameter indicating the degree of displacement of the worker in the direction of one or more latent features from the digital training task and determined by analysing the disparity matrix corresponding to the worker, with which said client device is associated; formation of a triplet of training objects containing a vector representation of a task, a vector representation of an employee, with which said client device is associated, and a digital training task label associated with a vector representation of an employee with which said client device is associated; using the training objects triplet to train the MLA algorithm to predict the digital task label for the vector representation of the digital task and the vector representation of the worker with which the client device is connected; at the stage of use: receiving a digital task by a server; determining, by the server, a vector representation of the task for the digital task; predicting, using the MLA algorithm, a plurality of digital task labels for the digital task based on a set of vector representations of workers with which the corresponding client devices are associated, and vector representation of task for digital task; server determines a digital task mark corresponding to at least one digital task mark from a plurality of digital task marks for the digital task.

EFFECT: formation of a more accurate marking of a digital task by the MLA algorithm due to preliminary training of the MLA algorithm using the generated triplet of training objects.

16 cl, 5 dwg