Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...

Knowledge graphs and ontologies form the backbone of the Semantic Web by enabling the structured representation and interconnection of data across diverse domains. These frameworks allow for the ...

During the Build 2017 Day 2 keynote in May, Microsoft execs repeatedly referenced Microsoft Graph, the successor to Office Graph, as the key enabler of next-generation computing scenarios. Graph (the ...

Polyglot persistence is becoming the norm in big data. Gone are the days when relational databases were the one store to rule them all; now the notion of using stores with data models that best align ...

Expanders graphs are sparse but well-connected. These seemingly contrasting properties have led to many applications in theoretical computer science, from complexity ...

Graph databases represent one of the fastest-growing areas in the database market. MarketsandMarkets’ report on graph databases predicts that graph databases will grow from $1.9 billion in 2021 to ...

Understanding the relationships in graph database theory allows us to work with the new 'shape' of data itself. Businesspeople like graphs. C-suite executives are fond of pie charts, Venn diagrams, ...

SAN FRANCISCO--(BUSINESS WIRE)--Apollo GraphQL, the pioneer in the use of open source and commercial GraphQL API technologies, announced today a $130 million Series D funding round led by New ...

The Graph, a project that says it's sometimes called the Google of Web3, has come out with a new roadmap, outlining new features the network will add as it characterizes itself as the leader of ...