Network Graph Analysis and Visualization with Gephi

Network Graph Analysis and Visualization with Gephi

A practical, hands-on guide, that provides you with all the tools you need to visualize and analyze your data using network graphs with Gephi.This book is for data analysts who want to intuitively reveal patterns and trends, highlight ...

Author: Ken Cherven

Publisher: Packt Publishing Ltd

ISBN: 9781783280148

Category: Computers

Page: 116

View: 363

A practical, hands-on guide, that provides you with all the tools you need to visualize and analyze your data using network graphs with Gephi.This book is for data analysts who want to intuitively reveal patterns and trends, highlight outliers, and tell stories with their data using Gephi. It is great for anyone looking to explore interactions within network datasets, whether the data comes from social media or elsewhere. It is also a valuable resource for those seeking to learn more about Gephi without being overwhelmed by technical details.
Categories: Computers

Graph Analysis and Visualization

Graph Analysis and Visualization

This book brings those proven techniques into the world of business, finance, strategy, and design, helping extract more information from data and better communicate the results to decision-makers.

Author: Richard Brath

Publisher: John Wiley & Sons

ISBN: 9781118845844

Category: Computers

Page: 544

View: 699

Wring more out of the data with a scientific approach to analysis Graph Analysis and Visualization brings graph theory out of the lab and into the real world. Using sophisticated methods and tools that span analysis functions, this guide shows you how to exploit graph and network analytic techniques to enable the discovery of new business insights and opportunities. Published in full color, the book describes the process of creating powerful visualizations using a rich and engaging set of examples from sports, finance, marketing, security, social media, and more. You will find practical guidance toward pattern identification and using various data sources, including Big Data, plus clear instruction on the use of software and programming. The companion website offers data sets, full code examples in Python, and links to all the tools covered in the book. Science has already reaped the benefit of network and graph theory, which has powered breakthroughs in physics, economics, genetics, and more. This book brings those proven techniques into the world of business, finance, strategy, and design, helping extract more information from data and better communicate the results to decision-makers. Study graphical examples of networks using clear and insightful visualizations Analyze specifically-curated, easy-to-use data sets from various industries Learn the software tools and programming languages that extract insights from data Code examples using the popular Python programming language There is a tremendous body of scientific work on network and graph theory, but very little of it directly applies to analyst functions outside of the core sciences – until now. Written for those seeking empirically based, systematic analysis methods and powerful tools that apply outside the lab, Graph Analysis and Visualization is a thorough, authoritative resource.
Categories: Computers

R Data Analysis and Visualization

R  Data Analysis and Visualization

In this chapter, you will learn the algorithms written in R for graph mining and
network analysis. In this chapter, we will cover the following topics: • Graph
mining • Mining frequent subgraph patterns • Social network mining • Social
influence ...

Author: Tony Fischetti

Publisher: Packt Publishing Ltd

ISBN: 9781786460486

Category: Computers

Page: 1783

View: 977

Master the art of building analytical models using R About This Book Load, wrangle, and analyze your data using the world's most powerful statistical programming language Build and customize publication-quality visualizations of powerful and stunning R graphs Develop key skills and techniques with R to create and customize data mining algorithms Use R to optimize your trading strategy and build up your own risk management system Discover how to build machine learning algorithms, prepare data, and dig deep into data prediction techniques with R Who This Book Is For This course is for data scientist or quantitative analyst who are looking at learning R and take advantage of its powerful analytical design framework. It's a seamless journey in becoming a full-stack R developer. What You Will Learn Describe and visualize the behavior of data and relationships between data Gain a thorough understanding of statistical reasoning and sampling Handle missing data gracefully using multiple imputation Create diverse types of bar charts using the default R functions Familiarize yourself with algorithms written in R for spatial data mining, text mining, and so on Understand relationships between market factors and their impact on your portfolio Harness the power of R to build machine learning algorithms with real-world data science applications Learn specialized machine learning techniques for text mining, big data, and more In Detail The R learning path created for you has five connected modules, which are a mini-course in their own right. As you complete each one, you'll have gained key skills and be ready for the material in the next module! This course begins by looking at the Data Analysis with R module. This will help you navigate the R environment. You'll gain a thorough understanding of statistical reasoning and sampling. Finally, you'll be able to put best practices into effect to make your job easier and facilitate reproducibility. The second place to explore is R Graphs, which will help you leverage powerful default R graphics and utilize advanced graphics systems such as lattice and ggplot2, the grammar of graphics. You'll learn how to produce, customize, and publish advanced visualizations using this popular and powerful framework. With the third module, Learning Data Mining with R, you will learn how to manipulate data with R using code snippets and be introduced to mining frequent patterns, association, and correlations while working with R programs. The Mastering R for Quantitative Finance module pragmatically introduces both the quantitative finance concepts and their modeling in R, enabling you to build a tailor-made trading system on your own. By the end of the module, you will be well-versed with various financial techniques using R and will be able to place good bets while making financial decisions. Finally, we'll look at the Machine Learning with R module. With this module, you'll discover all the analytical tools you need to gain insights from complex data and learn how to choose the correct algorithm for your specific needs. You'll also learn to apply machine learning methods to deal with common tasks, including classification, prediction, forecasting, and so on. Style and approach Learn data analysis, data visualization techniques, data mining, and machine learning all using R and also learn to build models in quantitative finance using this powerful language.
Categories: Computers

Handbook of Graph Drawing and Visualization

Handbook of Graph Drawing and Visualization

Visual analysis of bipartite biological networks. In Proceedings of ... Martin
Wattenberg. Centrality based visualization of small world graphs. ... Comparison
of visualizations in formal concept analysis and correspondence analysis. In
Michael ...

Author: Roberto Tamassia

Publisher: CRC Press

ISBN: 9781584884125

Category: Mathematics

Page: 862

View: 723

Get an In-Depth Understanding of Graph Drawing Techniques, Algorithms, Software, and Applications The Handbook of Graph Drawing and Visualization provides a broad, up-to-date survey of the field of graph drawing. It covers topological and geometric foundations, algorithms, software systems, and visualization applications in business, education, science, and engineering. Each chapter is self-contained and includes extensive references. The first several chapters of the book deal with fundamental topological and geometric concepts and techniques used in graph drawing, such as planarity testing and embedding, crossings and planarization, symmetric drawings, and proximity drawings. The following chapters present a large collection of algorithms for constructing drawings of graphs, including tree, planar straight-line, planar orthogonal and polyline, spine and radial, circular, rectangular, hierarchical, and three-dimensional drawings as well as labeling algorithms, simultaneous embeddings, and force-directed methods. The book then introduces the GraphML language for representing graphs and their drawings and describes three software systems for constructing drawings of graphs: OGDF, GDToolkit, and PIGALE. The final chapters illustrate the use of graph drawing methods in visualization applications for biological networks, computer security, data analytics, education, computer networks, and social networks. Edited by a pioneer in graph drawing and with contributions from leaders in the graph drawing research community, this handbook shows how graph drawing and visualization can be applied in the physical, life, and social sciences. Whether you are a mathematics researcher, IT practitioner, or software developer, the book will help you understand graph drawing methods and graph visualization systems, use graph drawing techniques in your research, and incorporate graph drawing solutions in your products.
Categories: Mathematics

Topological Methods in Data Analysis and Visualization IV

Topological Methods in Data Analysis and Visualization IV

Graph. 16(2), 248–260 (2010) 5. Bremer, P.T., Weber, G.H., Tierny, J., Pascucci,
V., Day, M., Bell, J.: Interactive exploration and analysis of large-scale simulations
using topology-based data segmentation. IEEE Trans. Vis. Comput. Graph.

Author: Hamish Carr

Publisher: Springer

ISBN: 9783319446844

Category: Mathematics

Page: 363

View: 154

This book presents contributions on topics ranging from novel applications of topological analysis for particular problems, through studies of the effectiveness of modern topological methods, algorithmic improvements on existing methods, and parallel computation of topological structures, all the way to mathematical topologies not previously applied to data analysis. Topological methods are broadly recognized as valuable tools for analyzing the ever-increasing flood of data generated by simulation or acquisition. This is particularly the case in scientific visualization, where the data sets have long since surpassed the ability of the human mind to absorb every single byte of data. The biannual TopoInVis workshop has supported researchers in this area for a decade, and continues to serve as a vital forum for the presentation and discussion of novel results in applications in the area, creating a platform to disseminate knowledge about such implementations throughout and beyond the community. The present volume, resulting from the 2015 TopoInVis workshop held in Annweiler, Germany, will appeal to researchers in the fields of scientific visualization and mathematics, domain scientists with an interest in advanced visualization methods, and developers of visualization software systems.
Categories: Mathematics

Security Data Visualization

Security Data Visualization

An introduction to a range of cyber security issues explains how to utilize graphical approaches to displaying and understanding computer security data, such as network traffic, server logs, and executable files, offering guidelines for ...

Author: Greg Conti

Publisher: No Starch Press

ISBN: 9781593271435

Category: Computers

Page: 272

View: 724

An introduction to a range of cyber security issues explains how to utilize graphical approaches to displaying and understanding computer security data, such as network traffic, server logs, and executable files, offering guidelines for identifying a network attack, how to assess a system for vulnerabilities with Afterglow and RUMINT visualization software, and how to protect a system from additional attacks. Original. (Intermediate)
Categories: Computers

A Primer in Biological Data Analysis and Visualization Using R

A Primer in Biological Data Analysis and Visualization Using R

Graphs in R are made by sending data variables to graphing functions. We refer
to these data, and anything else we send to a function, as arguments. In the
examples that follow you will see how data are sent to the graphing functions and
a ...

Author: Gregg Hartvigsen

Publisher: Columbia University Press

ISBN: 9780231537049

Category: Science

Page: 160

View: 658

R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data. Drawing on Gregg Hartvigsen's extensive experience teaching biostatistics and modeling biological systems, this text is an engaging, practical, and lab-oriented introduction to R for students in the life sciences. Underscoring the importance of R and RStudio in organizing, computing, and visualizing biological statistics and data, Hartvigsen guides readers through the processes of entering data into R, working with data in R, and using R to visualize data using histograms, boxplots, barplots, scatterplots, and other common graph types. He covers testing data for normality, defining and identifying outliers, and working with non-normal data. Students are introduced to common one- and two-sample tests as well as one- and two-way analysis of variance (ANOVA), correlation, and linear and nonlinear regression analyses. This volume also includes a section on advanced procedures and a chapter introducing algorithms and the art of programming using R.
Categories: Science

Analysis and Visualization of Biological Publication Data

Analysis and Visualization of Biological Publication Data

1.2.3 Visualisation of RDF The RDF data can be visualized as graphs as
mentioned before. There can be found ... RDF-Gravity stands for RDF GRAph
Visualization Tool and is a tool for visualizing directed graphs that are built in
RDF or OWL.

Author: Maren Lang

Publisher: diplom.de

ISBN: 9783836608688

Category: Computers

Page: 48

View: 597

Inhaltsangabe:Abstract: The content of today s World Wide Web is semantically not well structured. Every-thing is built for people and the data is therefore machine-readable but not machine- understandable. The semantic Web provides a solution for this problem through a new form of content structure. One technology for developing the Semantic Web is the Resource Description Framework (RDF). RDF is a language for representing information about resources in the World Wide Web and is particularly intended for representing metadata about Web resources. Therefore RDF provides interoperability between applications that exchange machine-understandable information on the Web. In this work, existing biological publication data which is stored in an object-relational database, is transformed into data represented in RDF. With the newly created RDF model it is possible to make a new way of queries, not only key word searching, but also queries with semantic sense. The additional advantage oft his representation is that it can be described not only in triples or XML structure but also in directed graphs. The World Wide Web provides documents that are built for human usage. There are formats like HTML, SVG and other extensions like Javascript or Javaapplets which are made for representing information. The content is semantically not well structured. These documents are structured for their presentation and are meant for people rather than computer which process data and information automatically. Everything is built for people and the data therefore is machine-readable but not machine-understandable. The Semantic Web provides a solution for this problem through a new form of structuring the content of the Web. It is not a separate Web but an extension of the existing one. There is, beside the documents of the Web, well defined additional information, which the computer is able to exploit automatically. This will give search engines more selective results as answer to the user enquired queries. Current search engines normally provide a big quantity of results to which the user has not or hardly referred initially. Their criteria of assigning a document to the set of relevant documents are the occurrences of one or several keywords. The results could be more precise if additional information which concerns the question would be considered. For example if somebody searches a document of mister Miller, the search engine could take into account, that one [...]
Categories: Computers

Topological Methods in Data Analysis and Visualization III

Topological Methods in Data Analysis and Visualization III

As mentioned above, we trimmed the pore graph by 5 mm from each side to
eliminate boundary effects. This is important for the final analysis of the pore
space, because the constrictions on edges near the boundaries exhibit
unrealistic radius ...

Author: Peer-Timo Bremer

Publisher: Springer Science & Business

ISBN: 9783319040998

Category: Mathematics

Page: 279

View: 374

This collection of peer-reviewed conference papers provides comprehensive coverage of cutting-edge research in topological approaches to data analysis and visualization. It encompasses the full range of new algorithms and insights, including fast homology computation, comparative analysis of simplification techniques, and key applications in materials and medical science. The volume also features material on core research challenges such as the representation of large and complex datasets and integrating numerical methods with robust combinatorial algorithms. Reflecting the focus of the TopoInVis 2013 conference, the contributions evince the progress currently being made on finding experimental solutions to open problems in the sector. They provide an inclusive snapshot of state-of-the-art research that enables researchers to keep abreast of the latest developments and provides a foundation for future progress. With papers by some of the world’s leading experts in topological techniques, this volume is a major contribution to the literature in a field of growing importance with applications in disciplines that range from engineering to medicine.
Categories: Mathematics

Mastering Gephi Network Visualization

Mastering Gephi Network Visualization

One doesn't have to look far to recognize the enormous growth of network graphs
as a means to explore and explain ... Social Network Analysis (SNA) has
certainly been the most visible subset of network graph analysis, with thousands
of ...

Author: Ken Cherven

Publisher: Packt Publishing Ltd

ISBN: 9781783987351

Category: Computers

Page: 378

View: 788

This book is intended for anyone interested in advanced network analysis. If you wish to master the skills of analyzing and presenting network graphs effectively, then this is the book for you. No coding experience is required to use this book, although some familiarity with the Gephi user interface will be helpful.
Categories: Computers

Network Analysis and Visualization in R

Network Analysis and Visualization in R

This book provides a quick start guide to network analysis and visualization in R. You'll learn, how to: - Create static and interactive network graphs using modern R packages. - Change the layout of network graphs.

Author: Alboukadel Kassambara

Publisher: STHDA

ISBN: 9781981179671

Category:

Page: 39

View: 572

Social network analysis is used to investigate the inter-relationship between entities. Examples of network structures, include: social media networks, friendship networks and collaboration networks. This book provides a quick start guide to network analysis and visualization in R. You'll learn, how to: - Create static and interactive network graphs using modern R packages. - Change the layout of network graphs. - Detect important or central entities in a network graph. - Detect community (or cluster) in a network.
Categories:

Graph Based Clustering and Data Visualization Algorithms

Graph Based Clustering and Data Visualization Algorithms

... Component Analysis Incremental Grid Growing Linde-Buzo-Gray algorithm
Linear Discriminant Analysis Locally Linear Embedding Multidimensional
Scaling Mutual Neighbor Distance Neural Gas Neural Network Online
Visualization ...

Author: Ágnes Vathy-Fogarassy

Publisher: Springer Science & Business Media

ISBN: 9781447151586

Category: Computers

Page: 110

View: 946

This work presents a data visualization technique that combines graph-based topology representation and dimensionality reduction methods to visualize the intrinsic data structure in a low-dimensional vector space. The application of graphs in clustering and visualization has several advantages. A graph of important edges (where edges characterize relations and weights represent similarities or distances) provides a compact representation of the entire complex data set. This text describes clustering and visualization methods that are able to utilize information hidden in these graphs, based on the synergistic combination of clustering, graph-theory, neural networks, data visualization, dimensionality reduction, fuzzy methods, and topology learning. The work contains numerous examples to aid in the understanding and implementation of the proposed algorithms, supported by a MATLAB toolbox available at an associated website.
Categories: Computers

Spatial Complexity in Urban Design Research

Spatial Complexity in Urban Design Research

This book offers state-of-the-art ‘tools for thinking’ for urban designers, planners and decision-makers.

Author: Jamie O’Brien

Publisher: Routledge

ISBN: 9781317229063

Category: Science

Page: 156

View: 470

This book offers state-of-the-art ‘tools for thinking’ for urban designers, planners and decision-makers. Thematically it focuses on the contexts of problems in urban design and places community spaces at the heart of urban design research. The book provides practicable tools for network modelling and visualization in urban design research. Step-by-step examples take readers through methods for tracing the evolution of road networks, and their impacts on contemporary community spaces. Easy-to-follow guides to programming show how to process and plot community data sets as network graphs. They reveal how these can help to observe and represent the different ways in which community spaces are inter-connected. This book places these technological methods in the context of current theories of community formations. It considers how these cutting-edge tools for thinking in urban design research – comprising both theories and methods – could transform our understanding of community spaces as being complex, inter-dependent and socially meaningful assets. This book is pioneering in its analysis of the urban contexts to community formations, and in its argument for professional integration between urban and knowledge practitioners. Academics and professionals within the fields of design research, urban studies, spatial analysis, urban geography and sociology will benefit from reading this book.
Categories: Science

Graph Drawing

Graph Drawing

Visual Analysis of One-to-Many Matched Graphs* Emilio Di Giacomo, Walter
Didimo, Giuseppe Liotta, and Pietro ... a rich body of papers and systems about
simultaneous graph embeddings and visualizations of evolving graphs (see, e.g.,
[7, ...

Author: Ioannis G. Tollis

Publisher: Springer Science & Business Media

ISBN: 9783642002182

Category: Computers

Page: 460

View: 653

This book constitutes the proceedings of the 16th International Symposium on Graph Drawing, GD 2008, held in Heraklion, Crete, Greece, during September 21-24, 2008. The 31 long papers and 8 short papers presented together with 10 posters and two invited papers were carefully reviewed and selected from 83 submissions. The volume also includes a report on the Graph Drawing Contest which was held during the conference. An important aspect of the conference is bridging the gap between theoretical advances and implemented solutions of geometric representation of graphs and networks. It is motivated by those applications where it is crucial to visualize structural information as graphs.
Categories: Computers

Graph Drawing

Graph Drawing

Computer graphics and visualization have come a long way in developing
techniques and tools to support the human user in data analysis and
investigation. As stated by R. Hamming: ”The purpose of computing is insight, not
numbers”.

Author: Austria) Symposium on Graph Drawing 2001 (Vienna

Publisher: Springer Science & Business Media

ISBN: 9783540433095

Category: Computers

Page: 524

View: 137

This book constitutes the thoroughly refereed post-proceedings of the 9th International Symposium on Graph Drawing, GD 2001, held in Vienna, Austria, in September 2001. The 32 revised full papers presented were carefully reviewed and selected from 66 paper submissions. Also included are a corrected version of a paper from the predecessor volume, short reports on the software systems exhibition, two papers of the special session on graph exchange formats, and a report on the annual graph drawing contests. The papers are organized in topical sections on hierarchical drawing, planarity, crossing theory, compaction, planar graphs, symmetries, interactive drawing, representations, aesthetics, 2D- and 3D-embeddings, data visualization, floor planning, and planar drawing.
Categories: Computers

Visualization for Computer Security

Visualization for Computer Security

This paper presents GARNET (Graphical Attack graph and Reachability Network
Evaluation Tool), an interactive visualization tool that facilitates attack graph
analysis. It provides a simplified view of critical steps that can be taken by an
attacker ...

Author: John R. Goodall

Publisher: Springer Science & Business Media

ISBN: 9783540859314

Category: Computers

Page: 197

View: 159

This volumecontains the paperspresented at VizSec 2008, the 5th International Workshop on Visualization for Cyber Security, held on September 15, 2008 in Cambridge, Massachusetts, USA. VizSec 2008 was held in conjunction with the 11thInternationalSymposiumonRecentAdvancesinIntrusionDetection(RAID). There were 27 submissions to the long and short paper categories. Each submission was reviewed by at least 2 reviewers and, on average, 2.9 program committee members. The program committee decided to accept 18 papers. The program also included an invited talk and a panel. The keynote address was given by Ben Shneiderman, University of Maryland at College Park, on the topic InformationForensics: HarnessingVisualizationto SupportDiscovery.The panel, on the topic The Need for Applied Visualization in Information Security Today, wasorganizedandmoderatedbyTobyKohlenbergfromIntelCorporation. July 2008 John R. Goodall Conference Organization Program Chairs John R. Goodall Secure Decisions division of Applied Visions Gregory Conti United States Military Academy Kwan-Liu Ma University of California at Davis Program Committee Stefan Axelsson Blekinge Institute of Technology Richard Bejtlich General Electric Kris Cook Paci?c Northwest National Laboratory David Ebert Purdue University Robert Erbacher Utah State University Deborah Frincke Paci?c Northwest National Laboratory Carrie Gates CA Labs John Gerth Stanford University Barry Irwin Rhodes University Daniel Keim University of Konstanz Toby Kohlenberg Intel Corporation Stuart Kurkowski Air Force Institute of Technology Kiran Lakkaraju University of Illinois at Urbana-Champaign Ra?ael Marty Splunk Douglas Maughan Department of Homeland Security John McHugh Dalhousie University Penny Rheingans UMBC Lawrence Rosenblum National Science Foundation George Tadda Air Force Research Lab Daniel Tesone Applied Visions Alfonso Valdes SRI International
Categories: Computers

Topological Methods in Data Analysis and Visualization

Topological Methods in Data Analysis and Visualization

We present a novel algorithm for automatic parameterization of tubelike surfaces
of arbitrary genus, such as the surfaces of knots, trees, blood vessels, neurons, or
any tubular graph with a globally consistent stripe texture. Mathematically ...

Author: Valerio Pascucci

Publisher: Springer Science & Business Media

ISBN: 3642150144

Category: Mathematics

Page: 260

View: 143

Topology-based methods are of increasing importance in the analysis and visualization of datasets from a wide variety of scientific domains such as biology, physics, engineering, and medicine. Current challenges of topology-based techniques include the management of time-dependent data, the representation of large and complex datasets, the characterization of noise and uncertainty, the effective integration of numerical methods with robust combinatorial algorithms, etc. . The editors have brought together the most prominent and best recognized researchers in the field of topology-based data analysis and visualization for a joint discussion and scientific exchange of the latest results in the field. This book contains the best 20 peer-reviewed papers resulting from the discussions and presentations at the third workshop on "Topological Methods in Data Analysis and Visualization", held 2009 in Snowbird, Utah, US. The 2009 "TopoInVis" workshop follows the two successful workshops in 2005 (Slovakia) and 2007 (Germany).
Categories: Mathematics

Big Data Analytics

Big Data Analytics

Graphical Analysis and Visualization of Big Data in Business Domains Divanshu
Gupta, Avinash Sharma, Narayanan ... Most efforts towards analyzing Big Data
assume data parallel applications and handle the large volumes of data using ...

Author: Srinath Srinivasa

Publisher: Springer

ISBN: 9783319138206

Category: Computers

Page: 197

View: 526

This book constitutes the refereed conference proceedings of the Third International Conference on Big Data Analytics, BDA 2014, held in New Delhi, India, in December 2014. The 11 revised full papers and 6 short papers were carefully reviewed and selected from 35 submissions and cover topics on media analytics; geospatial big data; semantics and data models; search and retrieval; graphics and visualization; application-specific big data.
Categories: Computers

Information Visualization

Information Visualization

The graph drawing community has also contributed ways to match the layout of a
graph and the mental map of a user (Misue et al., 1995). Large-network analysis
and visualization software Pajek supports a function called timed networks for ...

Author: Chaomei Chen

Publisher: Springer Science & Business Media

ISBN: 1852337893

Category: Computers

Page: 316

View: 266

Information visualization is not only about creating graphical displays of complex and latent information structures. It also contributes to a broader range of cognitive, social, and collaborative activities. This is the first book to examine information visualization from this perspective. This 2nd edition continues the unique and ambitious quest for setting information visualization and virtual environments in a unifying framework. It pays special attention to the advances made over the last 5 years and potentially fruitful directions to pursue. It is particularly updated to meet the need for practitioners. The book is a valuable source for researchers and graduate students.
Categories: Computers