Cayley graphs, constructed from the algebraic structure of groups, provide a natural framework for exploring complex combinatorial properties. In these graphs, vertices represent group elements and ...

As we've been keeping track of the graph scene for a while now, a couple of things have started becoming apparent. One, graph is here to stay. Two, there's still some way to go to make the benefits of ...

Knowledge graphs are one of the most important technologies of the 2020s. Gartner predicted that the applications of graph processing and graph databases will grow at 100% annually over the next few ...

Science and data are interwoven in many ways. The scientific method has lent a good part of its overall approach and practices to data-driven analytics, software development, and data science. Now ...

CodeRabbit combines code graph analysis and the power of large language models to identify issues in pull requests and suggest improvements, or even generate those improvements in a new branch. Code ...

No-code Graph RAG employs autonomous agents to integrate enterprise data and domain knowledge with LLMs for context-rich, explainable conversations By leveraging knowledge graphs for retrieval ...