Graphs are everywhere. From technology to finance, they often model valuable information such as people, networks, biological pathways and more. Often, scientists and technologists need to come up ...

The primary purpose of this study is to present mathematical modeling methods inspired by graph theory operations and logic as a tool to structurally analyze the socio-economic composition of a city ...

A controlled test compared three nearly identical pages: one with strong schema, one with poor schema, and one with none. Only the page with well-implemented schema appeared in an AI Overview and ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Protein function prediction is essential for elucidating biological processes and ...

This project implements a custom Graph Data Structure in Java to solve two real-world problems involving pathfinding. It avoids external libraries and uses only core Java logic for BFS/DFS-based ...

Abstract: Graph neural network is a new neural network model in recent years, whose advantage lies in processing graph structure data. In the era of big data, people can collect a large amount of ...

Data structure for dynamic connectivity in undirected graphs. Supports adding and removing edges and checking whether two vertices are connected (there's a path between them) in polylogarithmic time.

Abstract: This paper presents OPT+Graph, a web-based program visualization tool to support learning programming graph data structure in C. This tool is developed based on pythontutor.com (OPT). The ...