Dev Conference by Neo4j
Session Track: Data Science
Session Time:
Session description
Join Otávio for an in-depth exploration into transforming traditional relational databases into dynamic knowledge graphs using Neo4j. This session will cover how we leverage Cypher, Python, LangChain, and large language models (LLMs) alongside Retrieval-Augmented Generation (RAG) to enhance job-matching processes. Participants will gain practical insights into converting relational data to knowledge graphs; implementing RAG for real-time, context-aware decision-making; and tackling the challenges of designing graph-based AI systems in the employment sector. This comprehensive talk is tailored for developers and data scientists eager to advance their skills in AI and graph technologies.
Senior Software Architect and Deep Learning Researcher
Otávio has 19 years of experience in Web Applications Development and 12 years as a professor in Computer Science under-graduating courses. He participated as a speaker in more than 100 events around the country (Brazil). Currently, he is a professor at UFG (one of the top 40 LATAM universities) and a PhD student in Computer Science, with Graph Neural Networks and RAG being his main areas of study.
