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Graph patterns ➤ Projecting subgraphs | LinkedIn
Graph patterns ➤ Projecting subgraphs | LinkedIn
LDBC TUC: a focus on graph data in China Shanghai -- We’ve recently come out of two long, interesting days at LDBC’s 18th Technical Users Committee meeting in Guangzhou, in southern China. This post largely concentrates on one point that came up twice at the meeting: how to define subgraphs to be ex
·linkedin.com·
Graph patterns ➤ Projecting subgraphs | LinkedIn
Triple your knowledge graph speed with RDF linked data and openCypher using Amazon Neptune Analytics | Amazon Web Services
Triple your knowledge graph speed with RDF linked data and openCypher using Amazon Neptune Analytics | Amazon Web Services
There are numerous publicly available Resource Description Framework (RDF) datasets that cover a wide range of fields, including geography, life sciences, cultural heritage, and government data. Many of these public datasets can be linked together by loading them into an RDF-compatible database. In this post, we demonstrate how to build knowledge graphs with RDF linked data and openCypher using Amazon Neptune Analytics.
·aws.amazon.com·
Triple your knowledge graph speed with RDF linked data and openCypher using Amazon Neptune Analytics | Amazon Web Services
GitHub - a-s-g93/neo4j-runway: End to end solution for migrating CSV data into a Neo4j graph using an LLM for the data discovery and graph data modeling stages.
GitHub - a-s-g93/neo4j-runway: End to end solution for migrating CSV data into a Neo4j graph using an LLM for the data discovery and graph data modeling stages.
End to end solution for migrating CSV data into a Neo4j graph using an LLM for the data discovery and graph data modeling stages. - a-s-g93/neo4j-runway
·github.com·
GitHub - a-s-g93/neo4j-runway: End to end solution for migrating CSV data into a Neo4j graph using an LLM for the data discovery and graph data modeling stages.
Graph-based metadata filtering for improving vector search in RAG applications
Graph-based metadata filtering for improving vector search in RAG applications
Optimizing vector retrieval with advanced graph-based metadata techniques using LangChain and Neo4j Editor's Note: the following is a guest blog post from Tomaz Bratanic, who focuses on Graph ML and GenAI research at Neo4j. Neo4j is a graph database and analytics company which helps organizations find hidden relationships and patterns
·blog.langchain.dev·
Graph-based metadata filtering for improving vector search in RAG applications