Gabor Szabo – författare

Harness the power of social media to predict customer behavior and improve sales Social media is the biggest source of Big Data. Because of this, 90% of Fortune 500 companies are investing in Big Data initiatives that will help them predict consumer behavior to produce better sales results. Social Media Data Mining and Analytics shows analysts how to use sophisticated techniques to mine social media data, obtaining the information they need to generate amazing results for their businesses.Social Media Data Mining and Analytics isn't just another book on the business case for social media. Rather, this book provides hands-on examples for applying state-of-the-art tools and technologies to mine social media - examples include Twitter, Wikipedia, Stack Exchange, LiveJournal, movie reviews, and other rich data sources. In it, you will learn: The four key characteristics of online services-users, social networks, actions, and contentThe full data discovery lifecycle-data extraction, storage, analysis, and visualizationHow to work with code and extract data to create solutionsHow to use Big Data to make accurate customer predictionsHow to personalize the social media experience using machine learningUsing the techniques the authors detail will provide organizations the competitive advantage they need to harness the rich data available from social media platforms.

Harness the power of social media to predict customer behavior and improve sales

Social media is the biggest source of Big Data. Because of this, 90% of Fortune 500 companies are investing in Big Data initiatives that will help them predict consumer behavior to produce better sales results. Social Media Data Mining and Analytics shows analysts how to use sophisticated techniques to mine social media data, obtaining the information they need to generate amazing results for their businesses.

Social Media Data Mining and Analytics isn''t just another book on the business case for social media. Rather, this book provides hands-on examples for applying state-of-the-art tools and technologies to mine social media - examples include Twitter, Wikipedia, Stack Exchange, LiveJournal, movie reviews, and other rich data sources. In it, you will learn:

The four key characteristics of online services-users, social networks, actions, and content The full data discovery lifecycle-data extraction, storage, analysis, and visualization How to work with code and extract data to create solutions How to use Big Data to make accurate customer predictions How to personalize the social media experience using machine learning

Using the techniques the authors detail will provide organizations the competitive advantage they need to harness the rich data available from social media platforms.

Harness the power of social media to predict customer behavior and improve sales

Social media is the biggest source of Big Data. Because of this, 90% of Fortune 500 companies are investing in Big Data initiatives that will help them predict consumer behavior to produce better sales results. Social Media Data Mining and Analytics shows analysts how to use sophisticated techniques to mine social media data, obtaining the information they need to generate amazing results for their businesses.

Social Media Data Mining and Analytics isn''t just another book on the business case for social media. Rather, this book provides hands-on examples for applying state-of-the-art tools and technologies to mine social media - examples include Twitter, Wikipedia, Stack Exchange, LiveJournal, movie reviews, and other rich data sources. In it, you will learn:

The four key characteristics of online services-users, social networks, actions, and content The full data discovery lifecycle-data extraction, storage, analysis, and visualization How to work with code and extract data to create solutions How to use Big Data to make accurate customer predictions How to personalize the social media experience using machine learning

Using the techniques the authors detail will provide organizations the competitive advantage they need to harness the rich data available from social media platforms.

This book collects the notes of the lectures given at the Advanced Course on Crossed Products, Groupoids, and Rokhlin dimension, that took place at the Centre de Recerca Matemàtica (CRM) from March 13 to March 17, 2017. The notes consist of three series of lectures. The first one was given by Dana Williams (Dartmouth College), and served as an introduction to crossed products of C*-algebras and the study of their structure. The second series of lectures was delivered by Aidan Sims (Wollongong), who gave an overview of the theory of topological groupoids (as a model for groups and group actions) and groupoid C*-algebras, with particular emphasis on the case of étale groupoids. Finally, the last series was delivered by Gábor Szabó (Copenhagen), and consisted of an introduction to Rokhlin type properties (mostly centered around the work of Hirshberg, Winter and Zacharias) with hints to the more advanced theory related to groupoids.

This book collects the notes of the lectures given at the Advanced Course on Crossed Products, Groupoids, and Rokhlin dimension, that took place at the Centre de Recerca Matemàtica (CRM) from March 13 to March 17, 2017. The notes consist of three series of lectures. The first one was given by Dana Williams (Dartmouth College), and served as an introduction to crossed products of C*-algebras and the study of their structure. The second series of lectures was delivered by Aidan Sims (Wollongong), who gave an overview of the theory of topological groupoids (as a model for groups and group actions) and groupoid C*-algebras, with particular emphasis on the case of étale groupoids. Finally, the last series was delivered by Gábor Szabó (Copenhagen), and consisted of an introduction to Rokhlin type properties (mostly centered around the work of Hirshberg, Winter and Zacharias) with hints to the more advanced theory related to groupoids.

Item Response Theory, though it has become a widely recognized tool in language testing research, is still not used frequently in practical language assessment projects. This book intends to provide a theoretical overview as well as to give practical guidance concerning the application of IRT in item bank building in a language testing context by presenting a particular project in a higher education setting.