Machine learning based list recommendations

Abstract

A machine learning engine may correlate user profile data and/or list item data with a service provider action that may lead to a particular user action with respect to a list item (e.g., a task item of a to-do list, a content item of a content item queue, etc.). For example, a task item performance application may process user profile data and/or task item profile data to generate training data. In addition, the machine learning engine may generate a task item performance model using the training data by identifying indicators that correlate with the particular user action. Additionally, the task item performance application may then use the task item performance model to suggest actions that may be performed by a service provider to increase the likelihood of the user performing the particular user action with respect to the list item. Further, the machine learning engine may also determine weights for individual indicators.