Graph Algorithms

Graph Algorithms

Author: Mark Needham

Publisher: "O'Reilly Media, Inc."

Published: 2019-05-16

Total Pages: 297

ISBN-13: 1492047635

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Discover how graph algorithms can help you leverage the relationships within your data to develop more intelligent solutions and enhance your machine learning models. You’ll learn how graph analytics are uniquely suited to unfold complex structures and reveal difficult-to-find patterns lurking in your data. Whether you are trying to build dynamic network models or forecast real-world behavior, this book illustrates how graph algorithms deliver value—from finding vulnerabilities and bottlenecks to detecting communities and improving machine learning predictions. This practical book walks you through hands-on examples of how to use graph algorithms in Apache Spark and Neo4j—two of the most common choices for graph analytics. Also included: sample code and tips for over 20 practical graph algorithms that cover optimal pathfinding, importance through centrality, and community detection. Learn how graph analytics vary from conventional statistical analysis Understand how classic graph algorithms work, and how they are applied Get guidance on which algorithms to use for different types of questions Explore algorithm examples with working code and sample datasets from Spark and Neo4j See how connected feature extraction can increase machine learning accuracy and precision Walk through creating an ML workflow for link prediction combining Neo4j and Spark


Graphs, Networks and Algorithms

Graphs, Networks and Algorithms

Author: Dieter Jungnickel

Publisher: Springer Science & Business Media

Published: 2013-06-29

Total Pages: 597

ISBN-13: 3662038226

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Revised throughout Includes new chapters on the network simplex algorithm and a section on the five color theorem Recent developments are discussed


Graph Algorithms

Graph Algorithms

Author: Shimon Even

Publisher: Cambridge University Press

Published: 2011-09-19

Total Pages: 203

ISBN-13: 1139504150

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Shimon Even's Graph Algorithms, published in 1979, was a seminal introductory book on algorithms read by everyone engaged in the field. This thoroughly revised second edition, with a foreword by Richard M. Karp and notes by Andrew V. Goldberg, continues the exceptional presentation from the first edition and explains algorithms in a formal but simple language with a direct and intuitive presentation. The book begins by covering basic material, including graphs and shortest paths, trees, depth-first-search and breadth-first search. The main part of the book is devoted to network flows and applications of network flows, and it ends with chapters on planar graphs and testing graph planarity.


Algorithms on Trees and Graphs

Algorithms on Trees and Graphs

Author: Gabriel Valiente

Publisher: Springer Science & Business Media

Published: 2013-04-17

Total Pages: 492

ISBN-13: 366204921X

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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.


Guide to Graph Algorithms

Guide to Graph Algorithms

Author: K Erciyes

Publisher: Springer

Published: 2018-04-13

Total Pages: 475

ISBN-13: 3319732358

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This clearly structured textbook/reference presents a detailed and comprehensive review of the fundamental principles of sequential graph algorithms, approaches for NP-hard graph problems, and approximation algorithms and heuristics for such problems. The work also provides a comparative analysis of sequential, parallel and distributed graph algorithms – including algorithms for big data – and an investigation into the conversion principles between the three algorithmic methods. Topics and features: presents a comprehensive analysis of sequential graph algorithms; offers a unifying view by examining the same graph problem from each of the three paradigms of sequential, parallel and distributed algorithms; describes methods for the conversion between sequential, parallel and distributed graph algorithms; surveys methods for the analysis of large graphs and complex network applications; includes full implementation details for the problems presented throughout the text; provides additional supporting material at an accompanying website. This practical guide to the design and analysis of graph algorithms is ideal for advanced and graduate students of computer science, electrical and electronic engineering, and bioinformatics. The material covered will also be of value to any researcher familiar with the basics of discrete mathematics, graph theory and algorithms.


Graph Algorithms in the Language of Linear Algebra

Graph Algorithms in the Language of Linear Algebra

Author: Jeremy Kepner

Publisher: SIAM

Published: 2011-01-01

Total Pages: 388

ISBN-13: 9780898719918

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The current exponential growth in graph data has forced a shift to parallel computing for executing graph algorithms. Implementing parallel graph algorithms and achieving good parallel performance have proven difficult. This book addresses these challenges by exploiting the well-known duality between a canonical representation of graphs as abstract collections of vertices and edges and a sparse adjacency matrix representation. This linear algebraic approach is widely accessible to scientists and engineers who may not be formally trained in computer science. The authors show how to leverage existing parallel matrix computation techniques and the large amount of software infrastructure that exists for these computations to implement efficient and scalable parallel graph algorithms. The benefits of this approach are reduced algorithmic complexity, ease of implementation, and improved performance.


Graphs, Algorithms, and Optimization, Second Edition

Graphs, Algorithms, and Optimization, Second Edition

Author: William Kocay

Publisher: CRC Press

Published: 2016-11-03

Total Pages: 430

ISBN-13: 1482251256

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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. ?


Algorithms and Models for the Web Graph

Algorithms and Models for the Web Graph

Author: Bogumił Kamiński

Publisher: Springer Nature

Published: 2020-06-02

Total Pages: 183

ISBN-13: 3030484785

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This book constitutes the proceedings of the 17th International Workshop on Algorithms and Models for the Web Graph, WAW 2020, held in Warsaw, Poland, in September 2020. The 12 full papers presented in this volume were carefully reviewed and selected from 19 submissions. The aim of the workshop was to further the understanding of graphs that arise from the Web and various user activities on the Web, and stimulate the development of high-performance algorithms and applications that exploit these graphs. Due to the corona pandemic the conference was postponed from June 2020 to September 2020.


Distributed Graph Algorithms for Computer Networks

Distributed Graph Algorithms for Computer Networks

Author: Kayhan Erciyes

Publisher: Springer Science & Business Media

Published: 2013-05-16

Total Pages: 328

ISBN-13: 1447151739

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This book presents a comprehensive review of key distributed graph algorithms for computer network applications, with a particular emphasis on practical implementation. Topics and features: introduces a range of fundamental graph algorithms, covering spanning trees, graph traversal algorithms, routing algorithms, and self-stabilization; reviews graph-theoretical distributed approximation algorithms with applications in ad hoc wireless networks; describes in detail the implementation of each algorithm, with extensive use of supporting examples, and discusses their concrete network applications; examines key graph-theoretical algorithm concepts, such as dominating sets, and parameters for mobility and energy levels of nodes in wireless ad hoc networks, and provides a contemporary survey of each topic; presents a simple simulator, developed to run distributed algorithms; provides practical exercises at the end of each chapter.


Graph Algorithms and Applications 3

Graph Algorithms and Applications 3

Author: Giuseppe Liotta

Publisher: World Scientific

Published: 2004-01-01

Total Pages: 418

ISBN-13: 9789812796608

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This book contains Volume 6 of the Journal of Graph Algorithms and Applications (JGAA) . JGAA is a peer-reviewed scientific journal devoted to the publication of high-quality research papers on the analysis, design, implementation, and applications of graph algorithms. Areas of interest include computational biology, computational geometry, computer graphics, computer-aided design, computer and interconnection networks, constraint systems, databases, graph drawing, graph embedding and layout, knowledge representation, multimedia, software engineering, telecommunications networks, user interfaces and visualization, and VLSI circuit design. Graph Algorithms and Applications 3 presents contributions from prominent authors and includes selected papers from the Symposium on Graph Drawing (1999 and 2000). All papers in the book have extensive diagrams and offer a unique treatment of graph algorithms focusing on the important applications. Contents: Triangle-Free Planar Graphs and Segment Intersection Graphs (N de Castro et al.); Traversing Directed Eulerian Mazes (S Bhatt et al.); A Fast Multi-Scale Method for Drawing Large Graphs (D Harel & Y Koren); GRIP: Graph Drawing with Intelligent Placement (P Gajer & S G Kobourov); Graph Drawing in Motion (C Friedrich & P Eades); A 6-Regular Torus Graph Family with Applications to Cellular and Interconnection Networks (M Iridon & D W Matula); and other papers. Readership: Researchers and practitioners in theoretical computer science, computer engineering, and combinatorics and graph theory.