Dynamic graph algorithms and data structures represent a vital research frontier in computer science, underpinning applications from network analysis to real-time system monitoring. These methods ...

Graph algorithms and sparsification techniques have emerged as pivotal tools in the analysis and optimisation of complex networked systems. These approaches focus on reducing the number of edges in a ...

In algorithms, as in life, negativity can be a drag. Consider the problem of finding the shortest path between two points on a graph — a network of nodes connected by links, or edges. Often, these ...

In the era of Big Data, the relationship between data are complex and large in scale. The relationship between various data objects is described as Vertex and Edge, where the Vertex represents the ...

If you’ve been making the same commute for a long time, you’ve probably settled on what seems like the best route. But “best” is a slippery concept. Perhaps one day there’s an accident or road closure ...

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: ...

In recent years, the Massively Parallel Computation (MPC) model has gained significant attention. However, most of distributed and parallel graph algorithms in the MPC model are designed for static ...

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 ...

What is Graph Technology and What Can it do for Financial Institutions? Graph technology has been a cornerstone of mathematics for centuries, and its application in financial institutions and fintechs ...