Recorded Wednesday, November 14: This is the 6th episode that continues TigerGraph's Graph Guru series, a free educational webinar series for developers and data scientists.
The old adage “birds of a feather, flock together” introduces the next major graph analytics algorithm: community detection. We are looking to establish groups of densely interconnected entities - such as a cluster of households in a geographic area that are part of a county, state or federal social benefit program, a group of doctors serving a cluster of patients for a particular condition such as diabetes or opioid addiction, and a set of customers connected by referrals or payments for an eCommerce, digital wallet app or ride sharing service application.
In this Graph Gurus episode, we use the TigerGraph Developer Edition to build a solution using the algorithm, “Community Detection” from the newly released TigerGraph Algorithm library. In this episode, we will:
- Explain the “Community Detection” graph analytics algorithm and review multiple use cases where it can be applied for sectors including: government, healthcare, banking, eCommerce, payments and ride sharing.
- Present a graph solution to perform community detection using GSQL.
- Review a real-life business use case for community detection using TigerGraph and GSQL.
Dr. Victor Lee, Director Product Management
Emma Liu, Product Manager
Huiting Su, Software Engineer