Abstract: Graph Machine Learning (GML) with Graph Databases (GDBs) has gained significant relevance in recent years, due to its ability to handle complex interconnected data and apply ML techniques ...
Abstract: This paper investigates a GraphRAG framework that integrates knowledge graphs into the Retrieval-Augmented Generation (RAG) architecture to enhance networking applications. While RAG has ...
This project includes a full MCP (Model Context Protocol) server that enables AI agents to interact with user story data through standardized tools.
Transform your documents into an intelligent knowledge base combining Neo4j's graph database with retrieval-augmented generation. Currently deployed with 12 technical books (30,006 chunks, 25.9 GB ...
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