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Practical Graph Analytics with Apache Giraph
Practical Graph Analytics with Apache Giraph

Practical Graph Analytics with Apache Giraph helps you build data mining and machine learning applications using the Apache Foundation’s Giraph framework for graph processing. This is the same framework as used by Facebook, Google, and other social media analytics operations to derive business value from vast amounts of...

Algorithms and Data Structures: The Basic Toolbox
Algorithms and Data Structures: The Basic Toolbox
Algorithms are at the heart of every nontrivial computer application, and algorithmics is a modern and active area of computer science. Every computer scientist and every professional programmer should know about the basic algorithmic toolbox: structures that allow efficient organization and retrieval of data, frequently used algorithms, and basic...
Graph Databases
Graph Databases
Graph databases address one of the great macroscopic business trends of today: leveraging complex and dynamic relationships in highly connected data to generate insight and competitive advantage. Whether we want to understand relationships between customers, elements in a telephone or data center network, entertainment...
Graph Theory (Graduate Texts in Mathematics)
Graph Theory (Graduate Texts in Mathematics)
and guided mainly by the Four-Colour Conjecture. The resolution of the conjecture by K. Appel and W. Haken in 1976, the year in which our first book Graph Theory with Applications appeared, marked a turning point in its history. Since then, the subject has experienced explosive growth, due in large measure to its role as an essential structure...
Algorithms Unlocked
Algorithms Unlocked

Have you ever wondered how your GPS can find the fastest way to your destination, selecting one route from seemingly countless possibilities in mere seconds? How your credit card account number is protected when you make a purchase over the Internet? The answer is algorithms. And how do these mathematical formulations translate themselves...

Optimizing Hadoop for MapReduce
Optimizing Hadoop for MapReduce

This book is the perfect introduction to sophisticated concepts in MapReduce and will ensure you have the knowledge to optimize job performance. This is not an academic treatise; it's an example-driven tutorial for the real world.

Overview

  • Optimize your MapReduce job performance
  • ...
Graph-Based Clustering and Data Visualization Algorithms (SpringerBriefs in Computer Science)
Graph-Based Clustering and Data Visualization Algorithms (SpringerBriefs in Computer Science)
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...
Graph Classification and Clustering Based on Vector Space Embedding
Graph Classification and Clustering Based on Vector Space Embedding
Due to the ability of graphs to represent properties of entities and binary relations at the same time, a growing interest in graph based object repre sentation can be observed in science and engineering. Yet, graphs are still not the common data structure in pattern recognition and related fields. The reason for this is twofold. First,...
Big Data Analytics with Spark: A Practitioner's Guide to Using Spark for Large Scale Data Analysis
Big Data Analytics with Spark: A Practitioner's Guide to Using Spark for Large Scale Data Analysis

Big Data Analytics with Spark is a step-by-step guide for learning Spark, which is an open-source fast and general-purpose cluster computing framework for large-scale data analysis. You will learn how to use Spark for different types of big data analytics projects, including batch, interactive, graph, and stream data analysis as well...

Graphing Data with R: An Introduction
Graphing Data with R: An Introduction

It’s much easier to grasp complex data relationships with a graph than by scanning numbers in a spreadsheet. This introductory guide shows you how to use the R language to create a variety of useful graphs for visualizing and analyzing complex data for science, business, media, and many other fields. You’ll learn methods...

Trustworthy Compilers (Quantitative Software Engineering Series)
Trustworthy Compilers (Quantitative Software Engineering Series)

The Most Complete, Real-World Guide to Compiler

Development—and the Principles of Trustworthy Compilers

Drawing on the author's over thirty years of expertise in compiler development, research, and instruction, Trustworthy Compilers introduces and analyzes the concept of trustworthy compilers and the principles...

Advanced Topics in Fuzzy Graph Theory (Studies in Fuzziness and Soft Computing (375))
Advanced Topics in Fuzzy Graph Theory (Studies in Fuzziness and Soft Computing (375))

This book builds on two recently published books by the same authors on fuzzy graph theory. Continuing in their tradition, it provides readers with an extensive set of tools for applying fuzzy mathematics and graph theory to social problems such as human trafficking and illegal immigration. Further, it especially focuses on advanced...

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