Methods and systems for generating training data for computer-executable machine learning algorithm within a computer-implemented crowdsource environment

Abstract

Non-limiting embodiments of the present technology are directed to a method and system for generating a training dataset. The method comprises: accessing data associated with a plurality of assessors executing digital tasks of a first type and digital tasks of a second type; generating, a first ranked list of assessors and a second ranked list of assessors based on their past performance; for a given one of the plurality of assessors: generating, a class score for the common class of digital tasks; acquiring a request for executing a digital task of a third type; ranking, the plurality of assessors based on respective class scores, the given one from the plurality of assessors being one of top ranked ones from the plurality of assessors; transmitting the digital task of the third type to the given one; generating the training data for the MLA based on a response from the given one.