Prescriptive meeting resource recommendation engine using calendar invite content

Abstract

A prescriptive meeting resource recommendation engine automatically learns participant and resource preferences in the context of given meeting input data using natural language features, and automatically recommends all relevant participants and resources (teleconferences, web meetings, links, etc.) to the meeting creator. The engine uses a feature data store to associate historical persons and historical resources with various natural language features, e.g., chargrams. As the host enters text in an invitation template (such as in the title field), the engine extracts current natural language features and computes current participant scores and current resource scores based on the current natural language features. A 'forgetfulness' routine is applied to the feature data store to phase out the influence of stale data. After receiving user confirmation, the system takes appropriate action such as electronically sending invitations to the recommended participants and making reservations for the recommended resources.