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 for improving a machine learning allergy diagnosis process is provided. The method includes identifying databases comprising data identifying menu items served by food establishments. Allergy data defining a food products associated with potential allergens is analyzed in real time and in response, baseline allergen indication software code for defining an allergen baseline indicator is generated. Ingredients of the menu items are analyzed with respect to the allergy data and allergen baseline levels for the ingredients determined. An allergen baseline level for each menu item is determined and an allergen alert software application for alerting a user with respect to each overall allergen assessment is generated.

Abstract: A system for improving a machine learning allergy diagnosis process is provided. The system implements a method that includes identifying databases comprising data identifying menu items served by food establishments. Allergy data defining a food products associated with potential allergens is analyzed in real time and in response, baseline allergen indication software code for defining an allergen baseline indicator is generated. Ingredients of the menu items are analyzed with respect to the allergy data and allergen baseline levels for the ingredients determined. An allergen baseline level for each menu item is determined and an allergen alert software application for alerting a user with respect to each overall allergen assessment is generated.

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 system for improving a machine learning allergy diagnosis process is provided. The system implements a method that includes identifying databases comprising data identifying menu items served by food establishments. Allergy data defining a food products associated with potential allergens is analyzed in real time and in response, baseline allergen indication software code for defining an allergen baseline indicator is generated. Ingredients of the menu items are analyzed with respect to the allergy data and allergen baseline levels for the ingredients determined. An allergen baseline level for each menu item is determined and an allergen alert software application for alerting a user with respect to each overall allergen assessment is generated.

Abstract: A method for improving a machine learning allergy diagnosis process is provided. The method includes identifying databases comprising data identifying menu items served by food establishments. Allergy data defining a food products associated with potential allergens is analyzed in real time and in response, baseline allergen indication software code for defining an allergen baseline indicator is generated. Ingredients of the menu items are analyzed with respect to the allergy data and allergen baseline levels for the ingredients determined. An allergen baseline level for each menu item is determined and an allergen alert software application for alerting a user with respect to each overall allergen assessment is generated.