Massive Graph Analytics Massive Graph Analytics
    • $92.99

Publisher Description

"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.

GENRE
Business & Personal Finance
RELEASED
2022
20 July
LANGUAGE
EN
English
LENGTH
590
Pages
PUBLISHER
CRC Press
SELLER
Taylor & Francis Group
SIZE
39.8
MB

More Books Like This

Computational Aspects and Applications in Large-Scale Networks Computational Aspects and Applications in Large-Scale Networks
2018
Tutorials on Emerging Methodologies and Applications in Operations Research Tutorials on Emerging Methodologies and Applications in Operations Research
2006
Business Intelligence Business Intelligence
2017
Gems of Combinatorial Optimization and Graph Algorithms Gems of Combinatorial Optimization and Graph Algorithms
2016
Dynamics of Information Systems: Mathematical Foundations Dynamics of Information Systems: Mathematical Foundations
2012
New Trends in Data Warehousing and Data Analysis New Trends in Data Warehousing and Data Analysis
2008

Other Books in This Series

Data Science Data Science
2022
Tree-Based Methods for Statistical Learning in R Tree-Based Methods for Statistical Learning in R
2022
Supervised Machine Learning for Text Analysis in R Supervised Machine Learning for Text Analysis in R
2021
Introduction to Environmental Data Science Introduction to Environmental Data Science
2023
Public Policy Analytics Public Policy Analytics
2021
Data Analytics Data Analytics
2021