Abstract: A method and system for determining a result for a task executed in a crowd-sourced environment is disclosed. The method comprises receiving, a plurality of results of the task having been submitted by a plurality of human assessors; receiving a quality score for each human assessor of the plurality of human assessors; generating a plurality of vector representations comprising a vector representation for each of the results; mapping, the plurality of vector representations into a vector space; clustering the plurality of vector representations into at least a first cluster and a second cluster; executing a machine learning algorithm configured to generate a first confidence parameter and a second confidence parameter; in response to a given one of the first confidence parameter and the second confidence parameter meeting a predetermined condition, generating, an aggregated vector representation; and selecting the aggregated vector representation as the result of the task.

Abstract: Disclosed are a method and a system for determining a response to a digital task in a computer-implemented crowd-sourced environment. The method comprises determining if a number of the plurality of responses to the digital task received meets a pre-determined minimum answer threshold; in response to the number of the plurality of responses to the digital task meeting the pre-determined minimum answer threshold, executing: for each of the plurality of responses generating, by the server, a confidence parameter representing a probability of an associated one of the plurality of responses being correct; ranking the plurality of responses based on the confidence parameter to determine a top response being associated with a highest confidence parameter; and in response to the highest confidence parameter being above a pre-determined minimum confidence threshold, assigning a value of the top response as a label for the digital task and terminating the digital task execution.

Abstract: Disclosed are a method and a system for determining a response to a digital task in a computer-implemented crowd-sourced environment. The method comprises determining if a number of the plurality of responses to the digital task received meets a pre-determined minimum answer threshold; in response to the number of the plurality of responses to the digital task meeting the pre-determined minimum answer threshold, executing: for each of the plurality of responses generating, by the server, a confidence parameter representing a probability of an associated one of the plurality of responses being correct; ranking the plurality of responses based on the confidence parameter to determine a top response being associated with a highest confidence parameter; and in response to the highest confidence parameter being above a pre-determined minimum confidence threshold, assigning a value of the top response as a label for the digital task and terminating the digital task execution.

Abstract: A method and system for determining a result for a task executed in a crowd-sourced environment is disclosed. The method comprises receiving, a plurality of results of the task having been submitted by a plurality of human assessors; receiving a quality score for each human assessor of the plurality of human assessors; generating a plurality of vector representations comprising a vector representation for each of the results; mapping, the plurality of vector representations into a vector space; clustering the plurality of vector representations into at least a first cluster and a second cluster; executing a machine learning algorithm configured to generate a first confidence parameter and a second confidence parameter; in response to a given one of the first confidence parameter and the second confidence parameter meeting a predetermined condition, generating, an aggregated vector representation; and selecting the aggregated vector representation as the result of the task.