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Social Network-Based Recommender Systems

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This book introduces novel techniques and algorithms necessary to support the formation of social networks. Concepts such as link prediction, graph patterns, recommendation systems based on user reputation, strategic partner selection, collaborative systems and network formation based on ‘social brokers’ are presented. Chapters cover a wide range of models and algorithms, including graph models and a personalized PageRank model. Extensive experiments and scenarios using real world datasets from GitHub, Facebook, Twitter, Google Plus and the European Union ICT research collaborations serve to enhance reader understanding of the material with clear applications. Each chapter concludes with an analysis and detailed summary. Social Network-Based Recommender Systems is designed as a reference for professionals and researchers working in social network analysis and companies working on recommender systems. Advanced-level students studying computer science, statistics or mathematics will also find this books useful as a secondary text.

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Advanced Analytics with Spark: Patterns for Learning from Data at Scale
Advanced Analytics with Spark: Patterns for Learning from Data at Scale

In this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by example.

You’ll start with an...

Practical Data Science with R
Practical Data Science with R

Summary

Practical Data Science with R lives up to its name. It explains basic principles without the theoretical mumbo-jumbo and jumps right to the real use cases you'll face as you collect, curate, and analyze the data crucial to the success of your business. You'll apply the R programming language...

A Primer on Scientific Programming with Python (Texts in Computational Science and Engineering)
A Primer on Scientific Programming with Python (Texts in Computational Science and Engineering)

The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and...


Python for Secret Agents - Second Edition
Python for Secret Agents - Second Edition

Gather, analyze, and decode data to reveal hidden facts using Python, the perfect tool for all aspiring secret agents

About This Book

  • Discover the essential features of Python programming: statements, variables, expressions, and many of the built-in data types
  • Use Python's standard...
Remote Pairing: Collaborative Tools for Distributed Development
Remote Pairing: Collaborative Tools for Distributed Development

You've heard about pair programming's benefits: fewer bugs, improved skills, and faster delivery. But what happens when you want to pair with someone in another city, country, or even hemisphere? With the right tools, you won't have to relocate to refactor. In this book, you'll learn techniques used by the most productive...

Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference (Addison-Wesley Data & Analytics)
Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference (Addison-Wesley Data & Analytics)

Master Bayesian Inference through Practical Examples and Computation–Without Advanced Mathematical Analysis

 

Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely...

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