It’s often assumed that Dijkstra’s algorithm, or the A* graph traversal algorithm is used, but the reality is that although these pure graph theory algorithms are decidedly influential, they ...

Big data demands scalable solutions. This book delves into graph-based algorithms in Python that tackle massive datasets. Using code examples, you’ll be able to leverage these techniques for big data ...

General graph algorithms: In this project we had to implement different general graph theory algorithms, such as: a general graph representation, solving a labyrinth, topological sort, connected & ...

We are living in the age of big data, and scalable solutions are a necessity. Network science leverages the power of graph theory and flexible data structures to analyze big data at scale. This book ...

Abstract: Solve challenging and computationally intensive analytics problems by leveraging network science and graph algorithms Key Features Learn how to wrangle different types of datasets and ...

In theory, it cannot be ruled out that the algorithms might run for longer than the age of the universe. But in practice, many algorithms seem to work just fine. Almost always.

Servatius is a discrete, or finite, mathematician, and her major tools are matroid and graph theory. Matroid theory, says Servatius, is essential in developing and speeding up algorithms that are used ...

In this paper, we adopt a novel topological approach to fault diagnosis. In our researches, global information will be introduced into electric power network, we are using mainly BFS of graph theory ...

The analysis of temporal graphs integrates elements from graph theory, algorithm design and data science, enabling researchers to explore phenomena such as transient connectivity, recursive ...