COGNITIVE MODELING APPARATUS FOR DETECTING AND ADJUSTING QUALITATIVE CONTEXTS ACROSS MULTIPLE DIMENSIONS FOR MULTIPLE ACTORS

摘要

The present design is directed to a system for detecting and adjusting qualitative contexts across multiple dimensions for multiple actors with cognitive computing techniques including a series of periodic execution components configured to operate over full or partial sets of received data, the series of periodic components comprising a peer to peer analyzer configured to detect anomalous behaviors among work-specific peer actors sharing similar types tasks, an actor behavior analyzer configured to examine change in an actor's behavior over time by comparing the similarity of past behavior and current behavior, a rate of change predictor configured to study changes in behavior over time for peer to peer performance according to the peer to peer analyzer, actor behavior change according to the actor behavior analyzer, and actor correlation analysis, and a semantic rule analyzer configured to encode conditional, provisional, cognitive, operational, and functional knowledge, and a plurality of signal managers.