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Neo4j in Action

Author : Tareq Abedrabbo

Publisher : Simon and Schuster

Page : 441 pages

File Size : 30,92 MB

Release : 2014-12-05

Category : Computers

ISBN : 1638351996

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Book Description

Summary Neo4j in Action is a comprehensive guide to Neo4j, aimed at application developers and software architects. Using hands-on examples, you'll learn to model graph domains naturally with Neo4j graph structures. The book explores the full power of native Java APIs for graph data manipulation and querying. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Much of the data today is highly connected—from social networks to supply chains to software dependency management—and more connections are continually being uncovered. Neo4j is an ideal graph database tool for highly connected data. It is mature, production-ready, and unique in enabling developers to simply and efficiently model and query connected data. About the Book Neo4j in Action is a comprehensive guide to designing, implementing, and querying graph data using Neo4j. Using hands-on examples, you'll learn to model graph domains naturally with Neo4j graph structures. The book explores the full power of native Java APIs for graph data manipulation and querying. It also covers Cypher, Neo4j's graph query language. Along the way, you'll learn how to integrate Neo4j into your domain-driven app using Spring Data Neo4j, as well as how to use Neo4j in standalone server or embedded modes. Knowledge of Java basics is required. No prior experience with graph data or Neo4j is assumed. What's Inside Graph database patterns How to model data in social networks How to use Neo4j in your Java applications How to configure and set up Neo4j About the Authors Aleksa Vukotic is an architect specializing in graph data models. Nicki Watt, Dominic Fox, Tareq Abedrabbo, and Jonas Partner work at OpenCredo, a Neo Technology partner, and have been involved in many projects using Neo4j. Table of Contents PART 1 INTRODUCTION TO NEO4J A case for a Neo4j database Data modeling in Neo4j Starting development with Neo4j The power of traversals Indexing the data PART 2 APPLICATION DEVELOPMENT WITH NEO4J Cypher: Neo4j query language Transactions Traversals in depth Spring Data Neo4j PART 3 NEO4J IN PRODUCTION Neo4j: embedded versus server mode



Graph Analysis and Visualization

Author : Richard Brath

Publisher : John Wiley & Sons

Page : 539 pages

File Size : 24,70 MB

Release : 2015-01-20

Category : Computers

ISBN : 1118845692

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Book Description

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.



Graph Algorithms

Author : Mark Needham

Publisher : O'Reilly Media

Page : 268 pages

File Size : 37,36 MB

Release : 2019-05-16

Category : Computers

ISBN : 1492047651

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Book Description

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



Graph Drawing

Author : Guiseppe Liotta

Publisher : Springer Science & Business Media

Page : 556 pages

File Size : 27,76 MB

Release : 2004-01-13

Category : Mathematics

ISBN : 3540208313

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Book Description

The 11th International Symposium on Graph Drawing (GD 2003) was held on September 21–24, 2003, at the Universit` a degli Studi di Perugia, Perugia, Italy. GD 2003 attracted 93 participants from academic and industrial institutions in 17 countries. In response to the call for papers, the program committee received 88 re- larsubmissionsdescribingoriginalresearchand/orsystemdemonstrations.Each submission was reviewed by at least 4 program committee members and c- ments were returned to the authors. Following extensive e-mail discussions, the program committee accepted 34 long papers (12 pages each in the proceedings) and 11 short papers (6 pages each in the proceedings). Also, 6 posters (2 pages each in the proceedings) were displayed in the conference poster gallery. In addition to the 88 submissions, the program committee also received a submission of special type, one that was not competing with the others for a time slot in the conference program and that collects selected open problems in graph drawing. The aim of this paper, which was refereed with particular care andUNCHANGEDtworoundsofrevisions,istostimulatefutureresearchinthe graph drawing community. The paper presents 42 challenging open problems in di?erentareasofgraphdrawingandcontainsmorethan120references.Although the length of the paper makes it closer to a journal version than to a conference extended abstract, we decided to include it in the conference proceedings so that it could easily reach in a short time the vast majority of the graph drawing community.



Graph-Powered Machine Learning

Author : Alessandro Nego

Publisher : Simon and Schuster

Page : 494 pages

File Size : 10,73 MB

Release : 2021-09-28

Category : Computers

ISBN : 1617295647

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Book Description

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 architectures, best design practices, optimization approaches, and common pitfalls. Key Features · The lifecycle of a machine learning project · Three end-to-end applications · Graphs in big data platforms · Data source modeling · Natural language processing, recommendations, and relevant search · Optimization methods Readers comfortable with machine learning basics. About the technology By organizing and analyzing your data as graphs, your applications work more fluidly with graph-centric algorithms like nearest neighbor or page rank where it's important to quickly identify and exploit relevant relationships. Modern graph data stores, like Neo4j or Amazon Neptune, are readily available tools that support graph-powered machine learning. Alessandro Negro is a Chief Scientist at GraphAware. With extensive experience in software development, software architecture, and data management, he has been a speaker at many conferences, such as Java One, Oracle Open World, and Graph Connect. He holds a Ph.D. in Computer Science and has authored several publications on graph-based machine learning.



Graph Databases

Author : Christos Tjortjis

Publisher : CRC Press

Page : 191 pages

File Size : 17,64 MB

Release : 2023-10-13

Category : Computers

ISBN : 100099659X

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Book Description

With social media producing such huge amounts of data, the importance of gathering this rich data, often called "the digital gold rush", processing it and retrieving information is vital. This practical book combines various state-of-the-art tools, technologies and techniques to help us understand Social Media Analytics, Data Mining and Graph Databases, and how to better utilize their potential. Graph Databases: Applications on Social Media Analytics and Smart Cities reviews social media analytics with examples using real-world data. It describes data mining tools for optimal information retrieval; how to crawl and mine data from Twitter; and the advantages of Graph Databases. The book is meant for students, academicians, developers and simple general users involved with Data Science and Graph Databases to understand the notions, concepts, techniques, and tools necessary to extract data from social media, which will aid in better information retrieval, management and prediction.



Graph Databases

Author : Ian Robinson

Publisher : "O'Reilly Media, Inc."

Page : 224 pages

File Size : 22,28 MB

Release : 2013-06-10

Category : Computers

ISBN : 1449356249

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Book Description

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



The Practitioner's Guide to Graph Data

Author : Denise Gosnell

Publisher : O'Reilly Media

Page : 420 pages

File Size : 42,22 MB

Release : 2020-03-20

Category : Computers

ISBN : 1492044040

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Book Description

Graph data closes the gap between the way humans and computers view the world. While computers rely on static rows and columns of data, people navigate and reason about life through relationships. This practical guide demonstrates how graph data brings these two approaches together. By working with concepts from graph theory, database schema, distributed systems, and data analysis, you’ll arrive at a unique intersection known as graph thinking. Authors Denise Koessler Gosnell and Matthias Broecheler show data engineers, data scientists, and data analysts how to solve complex problems with graph databases. You’ll explore templates for building with graph technology, along with examples that demonstrate how teams think about graph data within an application. Build an example application architecture with relational and graph technologies Use graph technology to build a Customer 360 application, the most popular graph data pattern today Dive into hierarchical data and troubleshoot a new paradigm that comes from working with graph data Find paths in graph data and learn why your trust in different paths motivates and informs your preferences Use collaborative filtering to design a Netflix-inspired recommendation system



Knowledge Graph and Semantic Computing: Knowledge Graph Empowers New Infrastructure Construction

Author : Bing Qin

Publisher : Springer Nature

Page : 339 pages

File Size : 41,92 MB

Release : 2021-10-28

Category : Computers

ISBN : 9811664714

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Book Description

This book constitutes the refereed proceedings of the 6th China Conference on Knowledge Graph and Semantic Computing, CCKS 2021, held in Guangzhou, China, in November 2021. The 19 revised full papers and 9 short papers presented were carefully reviewed and selected from 170 submissions. The papers are organized in topical sections on ​knowledge extraction: knowledge graph representation and reasoning; knowledge acquisition and knowledge graph construction; linked data, knowledge integration, and knowledge graph storage management; natural language understanding and semantic computing; knowledge graph applications: semantic search, question answering, dialogue, decision support, and recommendation; knowledge graph open resources.



Python for Graph and Network Analysis

Author : Mohammed Zuhair Al-Taie

Publisher : Springer

Page : 214 pages

File Size : 41,41 MB

Release : 2017-03-20

Category : Computers

ISBN : 3319530046

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Book Description

This research monograph provides the means to learn the theory and practice of graph and network analysis using the Python programming language. The social network analysis techniques, included, will help readers to efficiently analyze social data from Twitter, Facebook, LiveJournal, GitHub and many others at three levels of depth: ego, group, and community. They will be able to analyse militant and revolutionary networks and candidate networks during elections. For instance, they will learn how the Ebola virus spread through communities. Practically, the book is suitable for courses on social network analysis in all disciplines that use social methodology. In the study of social networks, social network analysis makes an interesting interdisciplinary research area, where computer scientists and sociologists bring their competence to a level that will enable them to meet the challenges of this fast-developing field. Computer scientists have the knowledge to parse and process data while sociologists have the experience that is required for efficient data editing and interpretation. Social network analysis has successfully been applied in different fields such as health, cyber security, business, animal social networks, information retrieval, and communications.