Modern Graph Theory Algorithms With Python

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Modern Graph Theory Algorithms with Python

Colleen M. Farrelly,Franck Kalala Mutombo
Modern Graph Theory Algorithms with Python Book PDF

Author : Colleen M. Farrelly,Franck Kalala Mutombo
Publisher : Packt Publishing Ltd
Page : 290 pages
File Size : 54,7 Mb
Release : 2024-06-07
Category : Computers
ISBN : 9781805120179

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Modern Graph Theory Algorithms with Python by Colleen M. Farrelly,Franck Kalala Mutombo Pdf

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 analytics problems into networks Leverage graph theoretic algorithms to analyze data efficiently Apply the skills you gain to solve a variety of problems through case studies in Python Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionWe 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 guides you through the basics of network science, showing you how to wrangle different types of data (such as spatial and time series data) into network structures. You’ll be introduced to core tools from network science to analyze real-world case studies in Python. As you progress, you’ll find out how to predict fake news spread, track pricing patterns in local markets, forecast stock market crashes, and stop an epidemic spread. Later, you’ll learn about advanced techniques in network science, such as creating and querying graph databases, classifying datasets with graph neural networks (GNNs), and mining educational pathways for insights into student success. Case studies in the book will provide you with end-to-end examples of implementing what you learn in each chapter. By the end of this book, you’ll be well-equipped to wrangle your own datasets into network science problems and scale solutions with Python.What you will learn Transform different data types, such as spatial data, into network formats Explore common network science tools in Python Discover how geometry impacts spreading processes on networks Implement machine learning algorithms on network data features Build and query graph databases Explore new frontiers in network science such as quantum algorithms Who this book is for If you’re a researcher or industry professional analyzing data and are curious about network science approaches to data, this book is for you. To get the most out of the book, basic knowledge of Python, including pandas and NumPy, as well as some experience working with datasets is required. This book is also ideal for anyone interested in network science and learning how graph algorithms are used to solve science and engineering problems. R programmers may also find this book helpful as many algorithms also have R implementations.

Algebraic Graph Algorithms

K. Erciyes
Algebraic Graph Algorithms Book PDF

Author : K. Erciyes
Publisher : Springer Nature
Page : 229 pages
File Size : 47,8 Mb
Release : 2021-11-17
Category : Computers
ISBN : 9783030878863

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Algebraic Graph Algorithms by K. Erciyes Pdf

This textbook discusses the design and implementation of basic algebraic graph algorithms, and algebraic graph algorithms for complex networks, employing matroids whenever possible. The text describes the design of a simple parallel matrix algorithm kernel that can be used for parallel processing of algebraic graph algorithms. Example code is presented in pseudocode, together with case studies in Python and MPI. The text assumes readers have a background in graph theory and/or graph algorithms.

Algorithms on Trees and Graphs

Gabriel Valiente
Algorithms on Trees and Graphs Book PDF

Author : Gabriel Valiente
Publisher : Springer Nature
Page : 392 pages
File Size : 54,8 Mb
Release : 2021-10-11
Category : Computers
ISBN : 9783030818852

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Algorithms on Trees and Graphs by Gabriel Valiente Pdf

Graph algorithms is a well-established subject in mathematics and computer science. Beyond classical application fields, such as approximation, combinatorial optimization, graphics, and operations research, graph algorithms have recently attracted increased attention from computational molecular biology and computational chemistry. Centered around the fundamental issue of graph isomorphism, this text goes beyond classical graph problems of shortest paths, spanning trees, flows in networks, and matchings in bipartite graphs. Advanced algorithmic results and techniques of practical relevance are presented in a coherent and consolidated way. This book introduces graph algorithms on an intuitive basis followed by a detailed exposition in a literate programming style, with correctness proofs as well as worst-case analyses. Furthermore, full C++ implementations of all algorithms presented are given using the LEDA library of efficient data structures and algorithms.

Graphs, Algorithms, and Optimization

William Kocay,Donald L. Kreher
Graphs Algorithms and Optimization Book PDF

Author : William Kocay,Donald L. Kreher
Publisher : CRC Press
Page : 504 pages
File Size : 44,6 Mb
Release : 2017-09-20
Category : Mathematics
ISBN : 9781351989121

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Graphs, Algorithms, and Optimization by William Kocay,Donald L. Kreher Pdf

Graph theory offers a rich source of problems and techniques for programming and data structure development, as well as for understanding computing theory, including NP-Completeness and polynomial reduction. A comprehensive text, Graphs, Algorithms, and Optimization features clear exposition on modern algorithmic graph theory presented in a rigorous yet approachable way. The book covers major areas of graph theory including discrete optimization and its connection to graph algorithms. The authors explore surface topology from an intuitive point of view and include detailed discussions on linear programming that emphasize graph theory problems useful in mathematics and computer science. Many algorithms are provided along with the data structure needed to program the algorithms efficiently. The book also provides coverage on algorithm complexity and efficiency, NP-completeness, linear optimization, and linear programming and its relationship to graph algorithms. Written in an accessible and informal style, this work covers nearly all areas of graph theory. Graphs, Algorithms, and Optimization provides a modern discussion of graph theory applicable to mathematics, computer science, and crossover applications.

Optimization Problems in Graph Theory

Boris Goldengorin
Optimization Problems in Graph Theory Book PDF

Author : Boris Goldengorin
Publisher : Springer
Page : 331 pages
File Size : 44,8 Mb
Release : 2018-09-27
Category : Mathematics
ISBN : 9783319948300

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Optimization Problems in Graph Theory by Boris Goldengorin Pdf

This book presents open optimization problems in graph theory and networks. Each chapter reflects developments in theory and applications based on Gregory Gutin’s fundamental contributions to advanced methods and techniques in combinatorial optimization. Researchers, students, and engineers in computer science, big data, applied mathematics, operations research, algorithm design, artificial intelligence, software engineering, data analysis, industrial and systems engineering will benefit from the state-of-the-art results presented in modern graph theory and its applications to the design of efficient algorithms for optimization problems. Topics covered in this work include: · Algorithmic aspects of problems with disjoint cycles in graphs · Graphs where maximal cliques and stable sets intersect · The maximum independent set problem with special classes · A general technique for heuristic algorithms for optimization problems · The network design problem with cut constraints · Algorithms for computing the frustration index of a signed graph · A heuristic approach for studying the patrol problem on a graph · Minimum possible sum and product of the proper connection number · Structural and algorithmic results on branchings in digraphs · Improved upper bounds for Korkel--Ghosh benchmark SPLP instances

Graph Machine Learning

Claudio Stamile,Aldo Marzullo,Enrico Deusebio
Graph Machine Learning Book PDF

Author : Claudio Stamile,Aldo Marzullo,Enrico Deusebio
Publisher : Packt Publishing Ltd
Page : 338 pages
File Size : 44,5 Mb
Release : 2021-06-25
Category : Computers
ISBN : 9781800206755

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Graph Machine Learning by Claudio Stamile,Aldo Marzullo,Enrico Deusebio Pdf

Build machine learning algorithms using graph data and efficiently exploit topological information within your models Key Features Implement machine learning techniques and algorithms in graph data Identify the relationship between nodes in order to make better business decisions Apply graph-based machine learning methods to solve real-life problems Book Description Graph Machine Learning will introduce you to a set of tools used for processing network data and leveraging the power of the relation between entities that can be used for predictive, modeling, and analytics tasks. The first chapters will introduce you to graph theory and graph machine learning, as well as the scope of their potential use. You'll then learn all you need to know about the main machine learning models for graph representation learning: their purpose, how they work, and how they can be implemented in a wide range of supervised and unsupervised learning applications. You'll build a complete machine learning pipeline, including data processing, model training, and prediction in order to exploit the full potential of graph data. After covering the basics, you'll be taken through real-world scenarios such as extracting data from social networks, text analytics, and natural language processing (NLP) using graphs and financial transaction systems on graphs. You'll also learn how to build and scale out data-driven applications for graph analytics to store, query, and process network information, and explore the latest trends on graphs. By the end of this machine learning book, you will have learned essential concepts of graph theory and all the algorithms and techniques used to build successful machine learning applications. What you will learn Write Python scripts to extract features from graphs Distinguish between the main graph representation learning techniques Learn how to extract data from social networks, financial transaction systems, for text analysis, and more Implement the main unsupervised and supervised graph embedding techniques Get to grips with shallow embedding methods, graph neural networks, graph regularization methods, and more Deploy and scale out your application seamlessly Who this book is for This book is for data scientists, data analysts, graph analysts, and graph professionals who want to leverage the information embedded in the connections and relations between data points to boost their analysis and model performance using machine learning. It will also be useful for machine learning developers or anyone who wants to build ML-driven graph databases. A beginner-level understanding of graph databases and graph data is required, alongside a solid understanding of ML basics. You'll also need intermediate-level Python programming knowledge to get started with this book.

Modern Graph Theory

Bela Bollobas
Modern Graph Theory Book PDF

Author : Bela Bollobas
Publisher : Springer Science & Business Media
Page : 408 pages
File Size : 47,9 Mb
Release : 2013-12-01
Category : Mathematics
ISBN : 9781461206194

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Modern Graph Theory by Bela Bollobas Pdf

An in-depth account of graph theory, written for serious students of mathematics and computer science. It reflects the current state of the subject and emphasises connections with other branches of pure mathematics. Recognising that graph theory is one of several courses competing for the attention of a student, the book contains extensive descriptive passages designed to convey the flavour of the subject and to arouse interest. In addition to a modern treatment of the classical areas of graph theory, the book presents a detailed account of newer topics, including Szemerédis Regularity Lemma and its use, Shelahs extension of the Hales-Jewett Theorem, the precise nature of the phase transition in a random graph process, the connection between electrical networks and random walks on graphs, and the Tutte polynomial and its cousins in knot theory. Moreover, the book contains over 600 well thought-out exercises: although some are straightforward, most are substantial, and some will stretch even the most able reader.

An Introduction to Computational Systems Biology

Karthik Raman
An Introduction to Computational Systems Biology Book PDF

Author : Karthik Raman
Publisher : CRC Press
Page : 359 pages
File Size : 49,8 Mb
Release : 2021-05-30
Category : Computers
ISBN : 9780429944529

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An Introduction to Computational Systems Biology by Karthik Raman Pdf

Emphasises a hands-on approach to modelling Strong emphasis on coding and software tools for systems biology Covers the entire spectrum of modelling, from static networks, to dynamic models Thoughtful exercises to test and enable student understanding of concepts Current chapters on exciting new developments like whole-cell modelling and community modelling

Graphs, Algorithms, and Optimization, Second Edition

William Kocay,Donald L. Kreher
Graphs Algorithms and Optimization Second Edition Book PDF

Author : William Kocay,Donald L. Kreher
Publisher : CRC Press
Page : 543 pages
File Size : 50,6 Mb
Release : 2016-11-03
Category : Mathematics
ISBN : 9781482251258

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Graphs, Algorithms, and Optimization, Second Edition by William Kocay,Donald L. Kreher Pdf

The second edition of this popular book presents the theory of graphs from an algorithmic viewpoint. The authors present the graph theory in a rigorous, but informal style and cover most of the main areas of graph theory. The ideas of surface topology are presented from an intuitive point of view. We have also included a discussion on linear programming that emphasizes problems in graph theory. The text is suitable for students in computer science or mathematics programs. ?

Modern Applications of Graph Theory

Vadim Zverovich
Modern Applications of Graph Theory Book PDF

Author : Vadim Zverovich
Publisher : Oxford University Press
Page : 417 pages
File Size : 54,9 Mb
Release : 2021
Category : Mathematics
ISBN : 9780198856740

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Modern Applications of Graph Theory by Vadim Zverovich Pdf

This book discusses many modern, cutting-edge applications of graph theory, such as traffic networks and Braess' paradox, navigable networks and optimal routing for emergency response, backbone/dominating sets in wireless sensor networks, placement of electric vehicle charging stations, pedestrian safety and graph-theoretic methods in molecular epidemiology. Because of the rapid growth of research in this field, the focus of the book is on the up-to-date development of the aforementioned applications. The book will be ideal for researchers, engineers, transport planners and emergency response specialists who are interested in the recent development of graph theory applications. Moreover, this book can be used as teaching material for postgraduate students because, in addition to up-to-date descriptions of the applications, it includes exercises and their solutions. Some of the exercises mimic practical, real-life situations. Advanced students in graph theory, computer science or molecular epidemiology may use the problems and research methods presented in this book to develop their final-year projects, master's theses or doctoral dissertations; however, to use the information effectively, special knowledge of graph theory would be required.

Algorithms and Data Structures with Python

Cuantum Technologies LLC
Algorithms and Data Structures with Python Book PDF

Author : Cuantum Technologies LLC
Publisher : Packt Publishing Ltd
Page : 488 pages
File Size : 41,8 Mb
Release : 2024-06-12
Category : Computers
ISBN : 9781836208549

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Algorithms and Data Structures with Python by Cuantum Technologies LLC Pdf

Master Python and elevate your algorithmic skills with this comprehensive course. From introductory concepts to advanced computational problems, learn how to efficiently solve complex challenges and optimize your code. Key Features Comprehensive introduction to Python programming and algorithms Detailed exploration of data structures and sorting/searching techniques Advanced topics including graph algorithms and computational problem-solving Book DescriptionBegin your journey with an introduction to Python and algorithms, laying the groundwork for more complex topics. You will start with the basics of Python programming, ensuring a solid foundation before diving into more advanced and sophisticated concepts. As you progress, you'll explore elementary data containers, gaining an understanding of their role in algorithm development. Midway through the course, you’ll delve into the art of sorting and searching, mastering techniques that are crucial for efficient data handling. You will then venture into hierarchical data structures, such as trees and graphs, which are essential for understanding complex data relationships. By mastering algorithmic techniques, you’ll learn how to implement solutions for a variety of computational challenges. The latter part of the course focuses on advanced topics, including network algorithms, string and pattern deciphering, and advanced computational problems. You'll apply your knowledge through practical case studies and optimizations, bridging the gap between theoretical concepts and real-world applications. This comprehensive approach ensures you are well-prepared to handle any programming challenge with confidence.What you will learn Master sorting and searching algorithms Implement hierarchical data structures like trees and graphs Apply advanced algorithmic techniques to solve complex problems Optimize code for efficiency and performance Understand and implement advanced graph algorithms Translate theoretical concepts into practical, real-world solutions Who this book is for This course is designed for a diverse group of learners, including technical professionals, software developers, computer science students, and data enthusiasts. It caters to individuals who have a basic understanding of programming and are eager to deepen their knowledge of Python and algorithms. Whether you're a recent graduate, or an experienced developer looking to expand your skill set, this course is tailored to meet the needs of all types of audiences. Ideal for those aiming to strengthen their algorithmic thinking and improve their coding efficiency.

Algorithmic Graph Theory

Alan Gibbons
Algorithmic Graph Theory Book PDF

Author : Alan Gibbons
Publisher : Cambridge University Press
Page : 280 pages
File Size : 42,8 Mb
Release : 1985-06-27
Category : Computers
ISBN : 0521288819

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Algorithmic Graph Theory by Alan Gibbons Pdf

An introduction to pure and applied graph theory with an emphasis on algorithms and their complexity.

Handbook of Research on Advanced Applications of Graph Theory in Modern Society

Pal, Madhumangal,Samanta, Sovan,Pal, Anita
Handbook of Research on Advanced Applications of Graph Theory in Modern Society Book PDF

Author : Pal, Madhumangal,Samanta, Sovan,Pal, Anita
Publisher : IGI Global
Page : 591 pages
File Size : 53,7 Mb
Release : 2019-08-30
Category : Computers
ISBN : 9781522593829

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Handbook of Research on Advanced Applications of Graph Theory in Modern Society by Pal, Madhumangal,Samanta, Sovan,Pal, Anita Pdf

In the world of mathematics and computer science, technological advancements are constantly being researched and applied to ongoing issues. Setbacks in social networking, engineering, and automation are themes that affect everyday life, and researchers have been looking for new techniques in which to solve these challenges. Graph theory is a widely studied topic that is now being applied to real-life problems. The Handbook of Research on Advanced Applications of Graph Theory in Modern Society is an essential reference source that discusses recent developments on graph theory, as well as its representation in social networks, artificial neural networks, and many complex networks. The book aims to study results that are useful in the fields of robotics and machine learning and will examine different engineering issues that are closely related to fuzzy graph theory. Featuring research on topics such as artificial neural systems and robotics, this book is ideally designed for mathematicians, research scholars, practitioners, professionals, engineers, and students seeking an innovative overview of graphic theory.

Graph Theory

Beril Sirmacek
Graph Theory Book PDF

Author : Beril Sirmacek
Publisher : BoD – Books on Demand
Page : 196 pages
File Size : 41,7 Mb
Release : 2018-01-31
Category : Mathematics
ISBN : 9789535137726

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Graph Theory by Beril Sirmacek Pdf

This book is prepared as a combination of the manuscripts submitted by respected mathematicians and scientists around the world. As an editor, I truly enjoyed reading each manuscript. Not only will the methods and explanations help you to understand more about graph theory, but I also hope you will find it joyful to discover ways that you can apply graph theory in your scientific field. I believe the book can be read from the beginning to the end at once. However, the book can also be used as a reference guide in order to turn back to it when it is needed. I have to mention that this book assumes the reader to have a basic knowledge about graph theory. The very basics of the theory and terms are not explained at the beginner level. I hope this book will support many applied and research scientists from different scientific fields.

Graph Theory, Combinatorics and Algorithms

Martin Charles Golumbic,Irith Ben-Arroyo Hartman
Graph Theory Combinatorics and Algorithms Book PDF

Author : Martin Charles Golumbic,Irith Ben-Arroyo Hartman
Publisher : Springer Science & Business Media
Page : 296 pages
File Size : 44,6 Mb
Release : 2006-03-30
Category : Mathematics
ISBN : 9780387250366

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Graph Theory, Combinatorics and Algorithms by Martin Charles Golumbic,Irith Ben-Arroyo Hartman Pdf

Graph Theory, Combinatorics and Algorithms: Interdisciplinary Applications focuses on discrete mathematics and combinatorial algorithms interacting with real world problems in computer science, operations research, applied mathematics and engineering. The book contains eleven chapters written by experts in their respective fields, and covers a wide spectrum of high-interest problems across these discipline domains. Among the contributing authors are Richard Karp of UC Berkeley and Robert Tarjan of Princeton; both are at the pinnacle of research scholarship in Graph Theory and Combinatorics. The chapters from the contributing authors focus on "real world" applications, all of which will be of considerable interest across the areas of Operations Research, Computer Science, Applied Mathematics, and Engineering. These problems include Internet congestion control, high-speed communication networks, multi-object auctions, resource allocation, software testing, data structures, etc. In sum, this is a book focused on major, contemporary problems, written by the top research scholars in the field, using cutting-edge mathematical and computational techniques.