NODES AI 2026: Graph Theory and Games: A Case Study on New York Times Connections

Join Shafik Quoraishee at NODES AI for this session: “Graph Theory and Games: A Case Study on New York Times Connections”.

This session will examine how graph structures can support machine-assisted puzzle-solving in the New York Times Connections game. The talk will show how puzzle elements, word relationships, and category patterns can be represented as a graph in Neo4j, giving AI systems a way to operate on links rather than isolated features. The session will outline how to build a Neo4j-backed workflow for clustering, semantic grouping, and NLP-driven similarity scoring. It will cover how to store embeddings, word associations, and candidate categories as nodes and relationships, and how to use Cypher queries or graph algorithms to guide solver decisions. Attendees will see how graph patterns help estimate puzzle complexity, highlight ambiguous groupings, and explain solver choices. The session will also discuss how graph insights can support game design analysis and help teams study how players interpret categories and word relationships.

Learn more about Neo4j: https://neo4j.com/
Get Started with Aura: https://neo4j.com/product/aura-agent/
Join Free, Self-Paced Online Learning: https://graphacademy.neo4j.com/

#Neo4j #NODESAI #GraphDatabase #AI #GenerativeAI #KnowledgeGraph