Researchers have developed IGA, an unsupervised graph alignment framework that uses isomorphism-aware neural networks to ...

Existing graph-based retrieval-augmented generation (RAG) systems represent knowledge with binary relations and rely primarily on semantic similarity for retrieval. This design struggles with ...

Machine learning models are often drowning in data, but the problem is not always the sheer volume of samples. Increasingly, ...

Graph technology has become a requirement for the modern enterprise. Companies in virtually every industry, from healthcare to energy to financial services, are applying the power of graph analytics ...

Graph neural networks (GNNs) are a type of neural network architecture and deep learning method that can help users analyze graphs, enabling them to make predictions based on the data described by a ...

Forbes contributors publish independent expert analyses and insights. I track enterprise software application development & data management. Jul 03, 2025, 10:43am EDT Business 3d tablet virtual growth ...

Machine learning, task automation and robotics are already widely used in business. These and other AI technologies are about to multiply, and we look at how organizations can best take advantage of ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. This eMag examines how architects can lead ...

Many organizations use data fabrics to connect disparate data sources to a central access point, regardless of their type or location. Some take this further by incorporating knowledge graphs into ...