{
"item_title" : "Graph Theoretic Approaches for Analyzing Large-Scale Social Networks",
"item_author" : [" Natarajan Meghanathan "],
"item_description" : "Social network analysis has created novel opportunities within the field of data science. The complexity of these networks requires new techniques to optimize the extraction of useful information. Graph Theoretic Approaches for Analyzing Large-Scale Social Networks is a pivotal reference source for the latest academic research on emerging algorithms and methods for the analysis of social networks. Highlighting a range of pertinent topics such as influence maximization, probabilistic exploration, and distributed memory, this book is ideally designed for academics, graduate students, professionals, and practitioners actively involved in the field of data science.",
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Graph Theoretic Approaches for Analyzing Large-Scale Social Networks
Overview
Social network analysis has created novel opportunities within the field of data science. The complexity of these networks requires new techniques to optimize the extraction of useful information. Graph Theoretic Approaches for Analyzing Large-Scale Social Networks is a pivotal reference source for the latest academic research on emerging algorithms and methods for the analysis of social networks. Highlighting a range of pertinent topics such as influence maximization, probabilistic exploration, and distributed memory, this book is ideally designed for academics, graduate students, professionals, and practitioners actively involved in the field of data science.
This item is Non-Returnable
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Details
- ISBN-13: 9781522528142
- ISBN-10: 1522528148
- Publisher: Igi Global Scientific Publishing
- Publish Date: July 2017
- Dimensions: 11 x 8.5 x 0.88 inches
- Shipping Weight: 2.59 pounds
- Page Count: 384
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