SYSTEMS AND METHODS FOR A CONTEXT AWARE CONVERSATIONAL AGENT BASED ON MACHINE-LEARNING

摘要

Example implementations are directed to systems and methods for a context aware conversational agent for self-learning. In an example implementation, a method includes generating a journaling model based on activity data and engagement data associated with one or more tasks of a user. The journaling model uses machine-learning to identify a context pattern using the activity data, and maps performance associated with the one or more tasks based at least on the engagement data. The method adaptively provides a prompt to gather additional engagement data based on the context pattern in view of real-time activity data, where the prompt is generated based on the journaling model. The journaling model is updated based on the additional engagement data.