Gephi Cookbook

Devangana Khokhar

  • 出版商: Packt Publishing
  • 出版日期: 2015-05-30
  • 售價: $1,600
  • 貴賓價: 9.5$1,520
  • 語言: 英文
  • 頁數: 305
  • 裝訂: Paperback
  • ISBN: 1783987405
  • ISBN-13: 9781783987405
  • 下單後立即進貨 (約3~4週)


Over 90 hands-on recipes to master the art of network analysis and visualization with Gephi

About This Book

  • Design and explore graphical networks using a wide range of Gephi features
  • Analyze the structure and properties of graphical networks without having to write any code
  • Learn to optimize the Gephi plugins for efficient data visualization

Who This Book Is For

If you want to learn network analysis and visualization along with graph concepts from scratch, then this book is for you. This is ideal for those of you with little or no understanding of Gephi and this domain, but will also be beneficial for those interested in expanding their knowledge and experience.

What You Will Learn

  • Install and configure Gephi on your system and understand its various features
  • Perform basic manipulation and exploration tasks on graphs
  • Understand various layout algorithms present by default in Gephi and the principles behind them
  • Explore the properties of graphical networks using numerous filters and statistical metrics available in Gephi
  • Import graph data from different sources and manipulate it directly in tabular formats
  • Use real-world datasets to better understand network analysis

In Detail

Gephi is an open source, user-friendly network visualization and analysis tool that provides numerous powerful features, making it easy for novices to get to grips with graph analysis quickly.

This book is your one-stop guide to learning Gephi's interactive networking and visualization, alongside the graph theory concepts that drive them. Each recipe walks you through a task and explains why and how it works. Starting with installing Gephi, you will learn how to begin analyzing a graph using Gephi's various features. You will discover how to make informed decisions using layout algorithms and filters, and perform statistical analysis with real-world datasets. This guide is an invaluable resource if you would like to plunge into the network analysis domain without having to learn how to code.