Abstract: A method and system for improving a machine learning task assignment process is provided to address productivity with respect to satisfaction. The method includes connecting hardware devices to a server system. Job related data associated with job roles for individuals is retrieved and associated with a time period. Work related items of the job related data are presented and selections for work related items are retrieved via selectors for the work items. Expected and actual satisfaction ratings for the work related items are received and analyzed in accordance with an order in which they are received. At least one work item is assigned to a user and a specialized memory repository is generated within a portion of a memory device. Results of the assignment are stored within the specialized memory repository. Self-learning software code for executing future task assignment processes is generated and modified based on reported satisfaction ratings.

Abstract: A method and system for improving a machine learning task assignment process is provided to address productivity with respect to satisfaction. The method includes connecting hardware devices to a server system. Job related data associated with job roles for individuals is retrieved and associated with a time period. Work related items of the job related data are presented and selections for work related items are retrieved via selectors for the work items. Expected and actual satisfaction ratings for the work related items are received and analyzed in accordance with an order in which they are received. At least one work item is assigned to a user and a specialized memory repository is generated within a portion of a memory device. Results of the assignment are stored within the specialized memory repository. Self-learning software code for executing future task assignment processes is generated and modified based on reported satisfaction ratings.