A method and system for completing a task executed in a crowd-sourced environment is disclosed. The method comprises, at a training phase: transmitting a training task to a plurality of users; acquiring a plurality of training results responsive to the training task; acquiring a respective user activity history associated with each user; for each of the plurality of training results, assigning a label value; generating a set of triples of training data; and training a machine learning algorithm, the training including, determining for each triples of data a set of features representative of a property of the triples of training data; and generating an inferred function based on the set of features, the inferred function being configured to determine a error parameter of a given result received from a given user to a given task.