Root Cause Analysis and Detection Systems on Correlated Events and High-Dimensional Data
Expert: Enver Özdemir
The project will implement a Root Cause Analysis and Detection system with parallel data pipelines for ingressing data, using multithreaded processing, an Explainable AI-based Diagnostic Model, and an explanation generator that utilizes Feature Importance Analysis and Transformer Model. The system will monitor the network in a top-down approach to detect malfunctions, promptly analyze them, and produce human-understandable explanations. Furthermore, this comprehensive analysis mechanism not only identifies network disruptions but also enables autonomous intervention, preventing any potential issues from causing significant impact.
