The goal of this repository is to provide an overview of knowledge graphs in the domain of biomedicine and of resources for their construction. This is achieved in four complementary ways: A survey ...

On August 29, 2025, the structured data general large model "LimiX" was officially announced as open-source, developed jointly by Professor Cui Peng's team from the Department of Computer Science at ...

Both graph databases and knowledge graphs “have similarities but serve different purposes,” said Shalvi Singh, senior product manager at Amazon AI. “Graph databases serve as the underlying ...

Learn how large language models like ChatGPT make knowledge graph creation accessible, revealing hidden connections in your data.

This isn't an issue but rather a feature request for consideration- an ensemble method for combining causal graphs ascertained through different discovery methods, like outlined in this paper- http ...

Refining ontology-based knowledge in a knowledge graph helped to partially address the shortcomings of structured knowledge generated from books. Additionally, they demonstrated how semantic reasoning ...

Learn when using entity-based SEO strategies can give you an edge – and how to implement them without wasting effort.

This paper presents a framework for utilizing maritime and shipping documents to construct a knowledge graph using GraphRAG, a hybrid tool combining graph-based retrieval and generation capabilities.

The evolution of web search engines offers an instructive example, showing how knowledge can be extracted from unstructured sources and refined over time into a structured, interconnected graph.

At a time when every enterprise looks to leverage generative artificial intelligence, data sites are turning their attention to graph databases and knowledge graphs. The global graph database market ...

The Causal Knowledge Graph integrates and stores the causal relationships and related knowledge contained within the data, enabling efficient decision-making based on data.