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What is Graph

Chapter 3
Enabling Blockchain Technology for Secure Networking and Communications
A structure made of vertices and edges connecting vertices.
Published in Chapter:
Extracting Insights From Bitcoin Transactions: Data Warehouse Modeling and Analytical Questions
Rim Moussa (University of Carthage, Tunisia) and Alfredo Cuzzocrea (University of Calabria, Italy)
Copyright: © 2021 |Pages: 21
DOI: 10.4018/978-1-7998-5839-3.ch003
Abstract
Bitcoin is the most well-known cryptocurrency. It was first released in 2009 by Satoshi Nakamoto. Bitcoin serves as a decentralized medium of digital exchange, with transactions verified and recorded in the blockchain. The latter is a public immutable distributed ledger that operates without the need of a trusted record keeping authority or a central intermediary. It provides OLTP capabilities with both atomic transactions and data durability guarantees for blockchain transactions. Blockchain ledgers were not designed to perform analytics questions. The availability of the entire bitcoin transaction history, stored in its public blockchain, offers interesting opportunities for analyzing the transactions to obtain insights on users/entities patterns and transactions patterns. For these purposes, the authors need to store and analyze cryptocurrency transactions in a data warehouse. In this chapter, they investigate public blockchain datasets, and they overview different data models for setting up a data warehouse appliance of cryptocurrencies.
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Chapter 2
Optimization of the Vertex Separation Problem with Genetic Algorithms
A graph is a mathematical abstraction of a collection of objects called vertices where some pairs of objects are connected by links called edges. In other words, a graph represents binary relations among the objects.
Published in Chapter: Optimization of the Vertex Separation Problem with Genetic Algorithms; From: Handbook of Research on Military, Aeronautical, and Maritime Logistics and Operations
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Chapter 13
Visualization in Learning: Perception, Aesthetics, and Pragmatism
Mathematical construction, which consists of the set of nodes and edges. Nodes usually represent investigated objects, while edges – the links (relations) between them. Graph is popular visualization method in many areas like science, business, medicine, or education.
Published in Chapter: Visualization in Learning: Perception, Aesthetics, and Pragmatism; From: Handbook of Research on Maximizing Cognitive Learning through Knowledge Visualization
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Chapter 12
Fuzzy Social Network Modeling for Influencing Consumer Behavior
Is set of nodes connected by edges. If the edges have a direction associated them it is called a directed graph.
Published in Chapter: Fuzzy Social Network Modeling for Influencing Consumer Behavior; From: Handbook of Research on Managing and Influencing Consumer Behavior
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Chapter 76
Disk-Based Search
A set of nodes connected through edges. The node at the head of an edge is called as the target and at the tail as the source. A graph can be undirected, i.e., it is always possible to return to the source through the same edge – the converse is a directed graph. If given beforehand in the form of adjacency lists (e.g., a road network), we call it an explicit graph. Implicit graphs – another name for ‘state spaces’ – are generated on-the-fly from a start node and a set of rules/actions to generate the new states (e.g., a checkers game).
Published in Chapter: Disk-Based Search; From: Encyclopedia of Artificial Intelligence
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Chapter 344
Clustering Methods for Detecting Communities in Networks
A graph is represented as a set of points (vertices) connected by lines (edges).
Published in Chapter: Clustering Methods for Detecting Communities in Networks; From: Encyclopedia of Information Science and Technology, Third Edition
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Chapter 12
General Model for Metrics Calculation and Behavior Prediction in the Manufacturing Industry: An Automated Machine Learning Approach
An abstract mathematical entity which possesses nodes and transitions. It is used to model systems with interactions between its various nodes. A manufacturing plant or a line are both examples of physical entities that can be described by a graph.
Published in Chapter: General Model for Metrics Calculation and Behavior Prediction in the Manufacturing Industry: An Automated Machine Learning Approach; From: Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry
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Chapter 17
Improved Laser Cutting Process in Textile-Automotive Industry
It is a set of objects called vertices or nodes connected by links called edges or arcs, which can represent binary relations between elements of a set. They are studied in graph theory. Typically, a graph is plotted as a set of points (vertices or nodes) connected by lines (edges).
Published in Chapter: Improved Laser Cutting Process in Textile-Automotive Industry; From: Handbook of Research on Managerial Strategies for Achieving Optimal Performance in Industrial Processes
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Chapter 603
Aspects of Various Community Detection Algorithms in Social Network Analysis
A graph is a network of nodes, or vertices, and their interconnections, or edges.
Published in Chapter: Aspects of Various Community Detection Algorithms in Social Network Analysis; From: Encyclopedia of Information Science and Technology, Fourth Edition
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Chapter 31
Discrete Networks as a Suitable Approach for the Analysis of Genetic Regulation
A collection of points and lines connecting a subset of them. The points of a graph are commonly known as vertices or nodes. Similarly, lines connecting the vertices of a graph are known as edges, arcs, or interactions.
Published in Chapter: Discrete Networks as a Suitable Approach for the Analysis of Genetic Regulation; From: Handbook of Research on Systems Biology Applications in Medicine
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Chapter 105
Fuzzy Graphs and Fuzzy Hypergraphs
A graph G = (V, E) is a mathematical structure consisting of two finite sets V and E. The elements of V are called vertices (or nodes), and the elements of E are called edges. Each edge has a set of one or two vertices associated to it, which are called its endpoints.
Published in Chapter: Fuzzy Graphs and Fuzzy Hypergraphs; From: Encyclopedia of Artificial Intelligence
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Chapter 6
Application of Odd-Even Congruence Graph Labeling in Secured Cyber Physical Systems
The graph comprises of vertices and edges to represent the mathematical structures to model pairwise relations between objects.
Published in Chapter: Application of Odd-Even Congruence Graph Labeling in Secured Cyber Physical Systems; From: Real-Time Applications of Machine Learning in Cyber-Physical Systems
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Chapter 8
Study and Analysis of Visual Saliency Applications Using Graph Neural Networks
A data structure that represents objects (nodes) and their relationships (edges).
Published in Chapter: Study and Analysis of Visual Saliency Applications Using Graph Neural Networks; From: Concepts and Techniques of Graph Neural Networks
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Chapter 1
Fundamentals of Graph for Graph Neural Network
In mathematics and computer science, a graph is a collection of points, called vertices or nodes, connected by lines or arcs, called edges. Graphs are often used to model relationships between objects, with the nodes representing the objects and the edges representing the relationships between them.
Published in Chapter: Fundamentals of Graph for Graph Neural Network; From: Concepts and Techniques of Graph Neural Networks
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Chapter 18
Using Graph Neural Network to Enhance Quality of Service Prediction
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Chapter 34
Spatial Network Databases
A set of nodes and a set of edges connecting such nodes.
Published in Chapter: Spatial Network Databases; From: Handbook of Research on Innovations in Database Technologies and Applications: Current and Future Trends
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