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Graph Databases
  • Language: en
  • Pages: 238

Graph Databases

Discover how graph databases can help you manage and query highly connected data. With this practical book, you’ll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build a database that can adapt as your business evolves, this book shows you how to apply the schema-free graph model to real-world problems. This second edition includes new code samples and diagrams, using the latest Neo4j syntax, as well as information on new functionality. Learn how different organizations are using graph databases to outperform their competitors. With this book’s da...

Graph Databases
  • Language: en
  • Pages: 224

Graph Databases

Discover how graph databases can help you manage and query highly connected data. With this practical book, you’ll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build a database that can adapt as your business evolves, this book shows you how to apply the schema-free graph model to real-world problems. Learn how different organizations are using graph databases to outperform their competitors. With this book’s data modeling, query, and code examples, you’ll quickly be able to implement your own solution. Model data with the Cypher query language and property graph model Learn best practices and common pitfalls when modeling with graphs Plan and implement a graph database solution in test-driven fashion Explore real-world examples to learn how and why organizations use a graph database Understand common patterns and components of graph database architecture Use analytical techniques and algorithms to mine graph database information

Information and Communication Technology for Intelligent Systems
  • Language: en
  • Pages: 780

Information and Communication Technology for Intelligent Systems

This book gathers papers addressing state-of-the-art research in all areas of information and communication technologies and their applications in intelligent computing, cloud storage, data mining and software analysis. It presents the outcomes of the Fourth International Conference on Information and Communication Technology for Intelligent Systems, which was held in Ahmedabad, India. Divided into two volumes, the book discusses the fundamentals of various data analysis techniques and algorithms, making it a valuable resource for researchers and practitioners alike.

Graph Data Science with Neo4j
  • Language: en
  • Pages: 289

Graph Data Science with Neo4j

Supercharge your data with the limitless potential of Neo4j 5, the premier graph database for cutting-edge machine learning Purchase of the print or Kindle book includes a free PDF eBook Key FeaturesExtract meaningful information from graph data with Neo4j's latest version 5Use Graph Algorithms into a regular Machine Learning pipeline in PythonLearn the core principles of the Graph Data Science Library to make predictions and create data science pipelines.Book Description Neo4j, along with its Graph Data Science (GDS) library, is a complete solution to store, query, and analyze graph data. As graph databases are getting more popular among developers, data scientists are likely to face such d...

Designing Data-Intensive Applications
  • Language: en
  • Pages: 614

Designing Data-Intensive Applications

Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the s...

Massive Graph Analytics
  • Language: en
  • Pages: 681

Massive Graph Analytics

  • Type: Book
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  • Published: 2022-07-20
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  • Publisher: CRC Press

"Graphs. Such a simple idea. Map a problem onto a graph then solve it by searching over the graph or by exploring the structure of the graph. What could be easier? Turns out, however, that working with graphs is a vast and complex field. Keeping up is challenging. To help keep up, you just need an editor who knows most people working with graphs, and have that editor gather nearly 70 researchers to summarize their work with graphs. The result is the book Massive Graph Analytics." — Timothy G. Mattson, Senior Principal Engineer, Intel Corp Expertise in massive-scale graph analytics is key for solving real-world grand challenges from healthcare to sustainability to detecting insider threats, cyber defense, and more. This book provides a comprehensive introduction to massive graph analytics, featuring contributions from thought leaders across academia, industry, and government. Massive Graph Analytics will be beneficial to students, researchers, and practitioners in academia, national laboratories, and industry who wish to learn about the state-of-the-art algorithms, models, frameworks, and software in massive-scale graph analytics.

Cloud Security: Concepts, Methodologies, Tools, and Applications
  • Language: en
  • Pages: 2218

Cloud Security: Concepts, Methodologies, Tools, and Applications

  • Type: Book
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  • Published: 2019-04-01
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  • Publisher: IGI Global

Cloud computing has experienced explosive growth and is expected to continue to rise in popularity as new services and applications become available. As with any new technology, security issues continue to be a concern, and developing effective methods to protect sensitive information and data on the cloud is imperative. Cloud Security: Concepts, Methodologies, Tools, and Applications explores the difficulties and challenges of securing user data and information on cloud platforms. It also examines the current approaches to cloud-based technologies and assesses the possibilities for future advancements in this field. Highlighting a range of topics such as cloud forensics, information privacy, and standardization and security in the cloud, this multi-volume book is ideally designed for IT specialists, web designers, computer engineers, software developers, academicians, researchers, and graduate-level students interested in cloud computing concepts and security.

Quick Hits for Teaching with Digital Humanities
  • Language: en
  • Pages: 302

Quick Hits for Teaching with Digital Humanities

Quick Hits for Teaching with Digital Humanities: Successful Strategies from Award-Winning Teachers is an edited collection of 24 articles that aims to introduce faculty, administrators, and staff to ways in which digital techniques from the arts, humanities, and social sciences can be incorporated in the classroom. These techniques can enhance learning and professional development experiences for undergraduate and graduate students and faculty alike. This essential handbook illustrates the breadth of digital humanities across the disciplines with rich examples that bring best practices to life. Anyone who teaches at an institution of higher learning will find entry into new digital paradigms. As the authors share simple and complex ways to introduce digital humanities into the classroom, they expand understandings of what constitutes these current technologies for learning.

Databases Illuminated
  • Language: en
  • Pages: 708

Databases Illuminated

Databases Illuminated, Fourth Edition is designed to help students integrate theoretical material with practical knowledge, using an approach that applies theory to practical database implementation.

Graph-Powered Machine Learning
  • Language: en
  • Pages: 494

Graph-Powered Machine Learning

At its core, machine learning is about efficiently identifying patterns and relationships in data. Many tasks, such as finding associations among terms so you can make accurate search recommendations or locating individuals within a social network who have similar interests, are naturally expressed as graphs. Graph-Powered Machine Learning introduces you to graph technology concepts, highlighting the role of graphs in machine learning and big data platforms. You'll get an in-depth look at techniques including data source modeling, algorithm design, link analysis, classification, and clustering. As you master the core concepts, you'll explore three end-to-end projects that illustrate architec...