Leveraging Knowledge Graphs For Classifying Incident Situations in ICT Systems

Abstract

The complexity of Information and Communications Technology (ICT) systems, such as enterprise or Internet access provider networks, entails uncertainty in causal reasoning for efficient incident management. In this work, we propose to use knowledge graphs and explicit representation of incident context to enable support teams to provide a quick and effective response to complex incident situations. Formal analysis and expert opinions are used to analyze challenges in providing knowledge about relationships between events and incidents in network operations. We make use of an RDF knowledge graph generated from a real industrial settings and representing the network topology in terms of equipments and applications, past incidents and their resolutions. We then demonstrate the effectiveness of using a graph embeddings-based classifier to categorize incident tickets based on context and link anomaly models with their logical representation.