Knowledge Tree
Neo4j
Facts (25)
Sources
Bridging the Gap Between LLMs and Evolving Medical Knowledge arxiv.org Jun 29, 2025 8 facts
referenceThe Neo4j property graph model consists of nodes (entities representing data points), relationships (directed, named connections between nodes), and properties (key-value pairs associated with nodes and relationships).
referenceHongcheng Huang and Ziyu Dong published 'Research on architecture and query performance based on distributed graph database neo4j' in 2013.
claimNeo4j's cloud-based accessibility allows for distributed access and knowledge sharing without local storage constraints.
claimThe AMG-RAG system stores the Medical Knowledge Graph (MKG) within a Neo4j database to leverage its graph query engine for efficient retrieval and analysis during inference.
referenceNeo4j, an open-source NoSQL graph database, enables constant-time traversals by explicitly storing relationships, which avoids costly table joins and optimizes deep relationship queries.
referenceGraph databases like Neo4j address the challenge of highly interconnected datasets by efficiently modeling and processing complex, evolving data structures using nodes, relationships, and properties.
procedureThe AMG-RAG system employs a dynamic Medical Knowledge Graph (MKG) construction method characterized by six key innovations: (1) Dynamic Node and Relationship Creation using semantic templates; (2) Bidirectional Relationships for flexible traversal; (3) Confidence-Based Relevance Scoring using textual annotations and quantitative scores; (4) Summarization with Reliability Indicators; (5) Thresholding for Quality Control; and (6) Integration with Neo4j for storage and querying.
claimNeo4j's graph-based architecture supports horizontal scaling for large-scale, relationship-intensive medical data.
How to Improve Multi-Hop Reasoning With Knowledge Graphs and ... neo4j.com Jun 18, 2025 7 facts
claimThe Neo4j LLM Knowledge Graph Builder is an online application that transforms unstructured content, such as PDFs, documents, URLs, and YouTube transcripts, into structured knowledge graphs stored in Neo4j.
referenceKey features of the Neo4j LLM Knowledge Graph Builder include multimodal ingestion (PDFs, HTML, transcripts, URLs, cloud buckets), schema configuration (preset, existing Neo4j schema, or LLM-inferred), integrated vector and graph retrieval for hybrid search, visualization via in-app viewer or Neo4j Bloom, and flexible deployment options (Neo4j Aura or local Docker Compose).
claimThe Neo4j LLM Knowledge Graph Builder integrates large language models, including OpenAI, Gemini, Claude, and Diffbot, with Neo4j’s graph-native storage and retrieval capabilities.
claimDevelopers using Neo4j can traverse graphs to follow relationships, retrieve metadata, apply filters, or aggregate results while maintaining access to unstructured content embedded in nodes.
claimThe Neo4j LLM Knowledge Graph Builder creates a lexical graph of documents and chunks with embeddings, alongside an entity graph containing nodes and relationships, both stored in a Neo4j database.
claimThe Neo4j LLM Knowledge Graph Builder uses the llm-graph-transformer module, which Neo4j contributed to LangChain, and supports other LangChain integrations for tasks like GraphRAG search.
claimNeo4j provides native integration of graph and vector search.
Construction of Knowledge Graphs: State and Challenges - arXiv arxiv.org 5 facts
claimCovidGraph is managed as a Neo4J database.
claimNeo4j provides a node classification pipeline for predicting classes of unlabeled nodes, but the resulting predictions are added as node properties, which necessitates a post-processing step to redefine the label.
referenceThe dstlr framework for scalable knowledge graph construction utilizes Apache Solr as a document store, Apache Spark for the extraction and completion layer, and Neo4j as the graph database.
claimProperty Graph Models are supported by graph database systems including Neo4j, JanusGraph, and TigerGraph, as well as processing frameworks like Oracle Labs PGX and Gradoop.
claimNeo4j is a graph database developed by Neo4j, Inc.
A survey on augmenting knowledge graphs (KGs) with large ... link.springer.com Nov 4, 2024 1 fact
claimNeo4j has integrated natural language processing tools that translate user queries into Cypher, the native graph query language of Neo4j, to increase the accessibility and usability of graph database systems for users without deep technical expertise.
Addressing common challenges with knowledge graphs - SciBite scibite.com 1 fact
claimSciBite consultants provide expertise in Stardog and Neo4J technologies to assist in selecting appropriate tools for knowledge graph applications.
Construction of intelligent decision support systems through ... - Nature nature.com Oct 10, 2025 1 fact
referenceThe Integrated Knowledge-Enhanced Decision Support system uses a hybrid architecture for knowledge representation that implements OWL 2 DL ontologies with Protégé to manipulate Neo4j graphs for query and traversal purposes.
Leveraging Knowledge Graphs and LLM Reasoning to Identify ... arxiv.org Jul 23, 2025 1 fact
referenceThe experimental evaluation of the LLM agent framework utilized OpenAI’s GPT-4o via Langchain QA chains, interacting with a Neo4j knowledge graph through LLM-generated Cypher queries, with configuration settings of temperature 0.0, top_p 0.95, and a 4096-token limit.
Enhancing LLMs with Knowledge Graphs: A Case Study - LinkedIn linkedin.com Nov 7, 2023 1 fact
accountThe authors of 'Enhancing LLMs with Knowledge Graphs: A Case Study' developed a system to store, query, and fact-check healthcare benefits documents using a knowledge graph, utilizing a technology stack consisting of Neo4j, Weaviate, Whisper, and Streamlit.