A couple of weeks ago, I attended and spoke at the first stop in the Neo4j GraphTour in Washington D.C. and I was able to get the best answer yet to a question that I’d been pondering: what’s the ...

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now DeepMind wants to enable neural networks to ...

A puzzle that has long flummoxed computers and the scientists who program them has suddenly become far more manageable. A new algorithm efficiently solves the graph isomorphism problem, computer ...

Graph algorithms and processing form the backbone of numerous applications across science and industry, ranging from social network analysis to large-scale data management. The field has evolved to ...

Graph labeling is a central topic in combinatorial optimisation that involves assigning numerical or categorical labels to vertices or edges of a graph subject to specific constraints. This framework ...

Motif-based graph local clustering is a popular method for graph mining tasks due to its various applications, such as community detection, network optimization and graph learning. However, the ...

A research team has developed a new technology that enables to process a large-scale graph algorithm without storing the graph in the main memory or on disks. A KAIST research team has developed a new ...

Like the core algorithm, Google’s Knowledge Graph periodically updates. But little has been known about how, when, and what it means — until now. I believe these updates consist of three things: ...

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 ...