LHRLAB/HyperGraphRAG
[NeurIPS 2025] Official resources of "HyperGraphRAG: Retrieval-Augmented Generation via Hypergraph-Structured Knowledge Representation".
This project helps researchers and knowledge workers enhance the accuracy of information retrieved from large text datasets. It takes a collection of text documents as input and organizes them into a hypergraph, enabling more nuanced and interconnected searches. The output is a highly relevant, contextually rich answer to complex queries, making it ideal for anyone needing precise information from extensive textual knowledge bases.
348 stars. No commits in the last 6 months.
Use this if you need to extract highly accurate and contextually rich answers to complex questions from a large collection of documents, where simple keyword searches fall short.
Not ideal if your needs are met by basic keyword search, or if your document collection is small and doesn't require sophisticated relational understanding.
Stars
348
Forks
59
Language
Python
License
MIT
Category
Last pushed
Sep 22, 2025
Commits (30d)
0
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