Abstract: The emerging field of graph learning, which aims to learn reasonable graph structures from data, plays a vital role in Graph Signal Processing (GSP) and finds applications in various data ...

This paper investigates allocation rules in graph-structured cooperative games (hereinafter referred to as graph games) by integrating the notion of network control. A component-restricted game and ...

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 TechRadar article noted that nearly 90% of enterprise information (documents, emails, videos) lies dormant in unstructured systems. This "dark data" isn't just neglected; it's a liability. GenAI ...

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 ...

Abstract: Graph models provide efficient tools to capture the underlying structure of data defined over networks. Many real-world network topologies are subject to change over time. Learning to model ...

Rajiv Shesh is the Chief Revenue Officer at HCLSoftware where he leads revenue growth & customer advocacy for Products & Platforms division. What’s really powering AI? High-quality data—foundational ...

For decades, enterprise data infrastructure focused on answering the question: “What happened in our business?” Business intelligence tools, data warehouses, and pipelines were built to surface ...

GraphFaker now supports fetching unstructured text data from Wikipedia via the new WikiFetcher. This issue proposes developing a simple tutorial to help users turn this raw data into a graph, ...

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 ...