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The Practitioner's Guide to Graph Data Applying Graph Thinking and Graph Technologies to Solve Complex Problems

technologies Use graph technology to build a Customer 360 application, the most popular graph data pattern today Dive into hierarchical data and;

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Graph Kernels

, software plus data resources, and an empirical comparison of state-of-the-art graph kernels. It is divided into two parts: the first part focuses;

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Spark GraphX in Action

implementations. Along the way, it details practical techniques for enhancing applications and applying machine learning algorithms to graph data;

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Guide to Graph Algorithms

comparative analysis of sequential, parallel and distributed graph algorithms - including algorithms for big data - and an investigation into the;

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Practical Graph Mining with R

to extracting interesting patterns from graph data. It covers many basic and advanced techniques for the identification of anomalous or;

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Apache Spark Graph Processing

processing from loading and transforming graph data to * Improve the scalability of your graphs with a variety of real-world applications with;

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Graph Databases in Action

graph databases as a product architect and a consultant. He's spent his career leveraging cutting-edge technologies to build software in complex;

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Handbook of Graph Theory, Combinatorial Optimization, and Algorithms

The fusion between graph theory and combinatorial optimization has led to theoretically profound and practically useful algorithms, yet;

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Querying Graphs

graph data model-the pre-dominant data model adopted by modern graph database systems. We aim especially to give a coherent and in-depth;

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Graph Algorithms Practical Examples in Apache Spark and Neo4j

Learn how graph algorithms can help you leverage relationships within your data to develop intelligent solutions and enhance your machine;

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Human Interaction with Graphs

-programmers to query such graph data repositories. In this book, we present recent developments in the emerging area of visual graph querying paradigm;

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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;

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Complex Networks

The Up-to-Date Guide to Complex Networks for Students, Researchers, and Practitioners Networks with complex and irregular;

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Graph Theory and its Applications to Problems of Society

services, and social inequalities. The author presents both traditional and relatively atypical graph-theoretical topics to best illustrate;

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Visualizing Graph Data

. Visualizing these graphs makes it possible to literally see the connections. The graph model consists of data elements, called nodes, and;

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Graph Data Mining

to discover useful information and knowledge from graph data. The complications of nodes, links and the semi-structure form present;

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Descriptive Complexity, Canonisation, and Definable Graph St

first part starts with an introduction to the background, from logic, complexity, and graph theory, and develops the theory up to first;

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Graph Data Management: Fundamental Issues and Recent Developments

in this area, both in applied and in fundamental subdomains. The topics covered range from a general introduction to graph data management, to;

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Applications of Graph Theory

Applications of Graph Theory gives an introduction on the subject of graph theory and the applications related to it. It explains the;

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Large-Scale Graph Processing Using Apache Giraph

describes the fundamental abstractions of the system, its programming models and various techniques for using the system to process graph data at;

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Graph Theory

; the algebraic structure of graphs; the combination of graph theory and unsupervised learning applied to social data mining; organising and;

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PySpark SQL Recipes

solutions to problems related to dataframes, data manipulation summarization, and exploratory analysis. You will improve your skills in graph data;

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A Java Library of Graph Algorithms and Optimization

Because of its portability and platform-independence, Java is the ideal computer programming language to use when working on graph;

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A Java Library of Graph Algorithms and Optimization

Because of its portability and platform-independence, Java is the ideal computer programming language to use when working on graph;

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Graph-Based Social Media Analysis

to the use of graph analysis in the study of social and digital media. It addresses an important scientific and technological challenge;

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Simulation for Applied Graph Theory Using Visual C++

Classes (MFC) libraries for Windows visualization. This book explains how to create a graph interactively, solve problems in graph theory with;

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Analysis of Complex Networks

Mathematical problems such as graph theory problems are of increasing importance for the analysis of modelling data in biomedical research;

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