Optimized Counting of Common Neighbors/Vertices in GSQL
By Prateek AgrawalGraph analytics plays a crucial role in finding hidden relationships within large datasets. One fundamental operation in this domain is calculating the number of common neighbors between pairs…
Graph-Powered Cybersecurity
If you're reading this, then your daily personal and work life is probably dependent on information that is stored and accessed digitally. People and processes are working around the clock…
Utilizing Multi-edge for Temporal Search in a Sales Agent Hierarchy
Introduction Hello everyone! I'm Xuanlei Lin. I have worked as a solution engineer at TigerGraph for two years and as a customer success consultant for another two years. Throughout this…
Advancing Entity Resolution for Fraud Detection with TigerGraph
First in our series of blogs straight from our engineers to you. In today's digitally interconnected world the proliferation of data has presented both unprecedented opportunities and challenges. One of…
Using Graph Machine Learning to Improve Fraud Detection Rates
by Parker Erickson Fraud comes in all shapes and forms across many industries; from account takeovers, to transaction fraud, the financial services industry to healthcare, fraud is both prevalent and…
How Two Forbes Top 20 Businesses Transformed Their Core Rules Engines
In today's rapidly evolving business landscape, agility and efficiency are crucial for staying competitive. To achieve this, businesses rely on rules engines to automate decision-making processes efficiently and consistently. However,…
Supercharging Fraud Detection: How a Leading Financial Institution Utilizes TigerGraph for Real-Time Entity Resolution
In today's fast-paced financial landscape, real-time fraud detection has become essential for safeguarding customer assets and preserving trust in financial institutions. One leading investment bank recently embraced an innovative solution…
- 1
- 2
- 3
- 4
- …
- 33
- Go to the next page
