Extraction of actionable insights through analysis of unstructured computer text

Abstract

Methods and apparatuses are described in which unstructured computer text is analyzed for extraction of actionable insights in a computing environment. A server executes a machine learning classification model on text messages exchanged between users to classify each text message according to a disposition and a theme. The server analyzes the classified messages to generate candidate work items, each associated with software applications and skills requirements. The server filters the candidate items to remove extraneous items based upon a work item backlog or a prioritization. The server determines team members to assign to each remaining candidate item by comparing the software applications and the skills requirements for the work item to a profile for each team member. The server creates a task for each remaining candidate item, the task including the assigned team members. The server generates a notification for each task for transmission to the assigned team members.