New AWS Software Competencies — Financial, Auto, GenAI, and ML | Learn Now

Neo4j logo

Nodes2024

Dev Conference by Neo4j

Register for NODES 24

You only need to register once to attend all sessions.

Enhancing Business Process Anomaly Detection With Neo4j and Graph Neural Networks

Session Track: Data Science

Session Time:

Session description

AnomalyNet is a framework for anomaly detection in business processes using graph neural networks (GNN) as a module of the Next4biz BPM platform. Leveraging of business process graphs stored on our Neo4j graph database enhances the efficiency of identifying process deviations and optimizing operations. In this session, the attendees will explore an anomaly detection study done on business event logs from real-life business processes. Participants will gain insights into advanced anomaly detection techniques and benefits of leveraging graph data structure. By attending, you will learn how you can leverage the power of graphs when working with business process data.

Speaker

photo of Teoman Berkay Ayaz

Teoman Berkay Ayaz

Data Scientist, Next4biz

Computer Engineering graduate & Published Researcher working in the core/ Data Science R&D for Next4biz, a leading CRM, CSM, and BPM software development company located in Istanbul, Turkey.