Practical Text Mining and Statistical Analysis for Non structured Text Data Applications

The world contains an unimaginably vast amount of digital information which is getting ever vaster ever more rapidly. This makes it possible to do many things that previously could not be done: spot business trends, prevent diseases, combat crime and so on. Managed well, the textual data can be used to unlock new sources of economic value, provide fresh insights into science and hold governments to account. As the Internet expands and our natural capacity to process the unstructured text that it contains diminishes, the value of text mining for information retrieval and search will increase dramatically. This comprehensive professional reference brings together all the information, tools and methods a professional will need to efficiently use text mining applications and statistical analysis. The Handbook of Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications presents a comprehensive how- to reference that shows the user how to conduct text mining and statistically analyze results. In addition to providing an in-depth examination of core text mining and link detection tools, methods and operations, the book examines advanced preprocessing techniques, knowledge representation considerations, and visualization approaches. Finally, the book explores current real-world, mission-critical applications of text mining and link detection using real world example tutorials in such varied fields as corporate, finance, business intelligence, genomics research, and counterterrorism activities. -Extensive case studies, most in a tutorial format, allow the reader to 'click through' the example using a software program, thus learning to conduct text mining analyses in the most rapid manner of learning possible -Numerous examples, tutorials, power points and datasets available via companion website on Elsevierdirect.com -Glossary of text mining terms provided in the appendix

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  • Author : Gary Miner
  • Publisher : Academic Press
  • Pages : 1053 pages
  • ISBN : 012386979X
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKPractical Text Mining and Statistical Analysis for Non structured Text Data Applications

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications
  • Author : Gary Miner
  • Publisher : Academic Press
  • Release : 06 May 2021
GET THIS BOOKPractical Text Mining and Statistical Analysis for Non-structured Text Data Applications

The world contains an unimaginably vast amount of digital information which is getting ever vaster ever more rapidly. This makes it possible to do many things that previously could not be done: spot business trends, prevent diseases, combat crime and so on. Managed well, the textual data can be used to unlock new sources of economic value, provide fresh insights into science and hold governments to account. As the Internet expands and our natural capacity to process the unstructured text

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications
  • Author : Gary Miner,John Elder IV,Andrew Fast,Thomas Hill,Robert Nisbet,Dursun Delen
  • Publisher : Academic Press
  • Release : 25 January 2012
GET THIS BOOKPractical Text Mining and Statistical Analysis for Non-structured Text Data Applications

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications brings together all the information, tools and methods a professional will need to efficiently use text mining applications and statistical analysis. Winner of a 2012 PROSE Award in Computing and Information Sciences from the Association of American Publishers, this book presents a comprehensive how-to reference that shows the user how to conduct text mining and statistically analyze results. In addition to providing an in-depth examination of core text mining and

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications
  • Author : Anonim
  • Publisher : Unknown Publisher
  • Release : 06 May 2021
GET THIS BOOKPractical Text Mining and Statistical Analysis for Non-structured Text Data Applications

The world contains an unimaginably vast amount of digital information which is getting ever vaster ever more rapidly. This makes it possible to do many things that previously could not be done: spot business trends, prevent diseases, combat crime and so on. Managed well, the textual data can be used to unlock new sources of economic value, provide fresh insights into science and hold governments to account. As the Internet expands and our natural capacity to process the unstructured text

Handbook of Statistical Analysis and Data Mining Applications

Handbook of Statistical Analysis and Data Mining Applications
  • Author : Robert Nisbet,Gary Miner,Ken Yale
  • Publisher : Elsevier
  • Release : 09 November 2017
GET THIS BOOKHandbook of Statistical Analysis and Data Mining Applications

Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and

Text Mining and Analysis

Text Mining and Analysis
  • Author : Dr. Goutam Chakraborty,Murali Pagolu,Satish Garla
  • Publisher : SAS Institute
  • Release : 22 November 2014
GET THIS BOOKText Mining and Analysis

Big data: It's unstructured, it's coming at you fast, and there's lots of it. In fact, the majority of big data is text-oriented, thanks to the proliferation of online sources such as blogs, emails, and social media. However, having big data means little if you can't leverage it with analytics. Now you can explore the large volumes of unstructured text data that your organization has collected with Text Mining and Analysis: Practical Methods, Examples, and Case Studies Using SAS. This

Text Data Management and Analysis

Text Data Management and Analysis
  • Author : ChengXiang Zhai,Sean Massung
  • Publisher : Morgan & Claypool
  • Release : 30 June 2016
GET THIS BOOKText Data Management and Analysis

Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. This has led to an increasing demand for powerful software tools to help people analyze and manage vast amounts of text data effectively and efficiently. Unlike data generated by a computer system or sensors, text data are usually generated directly by humans, and are accompanied

Practical Predictive Analytics and Decisioning Systems for Medicine

Practical Predictive Analytics and Decisioning Systems for Medicine
  • Author : Linda Miner,Pat Bolding,Joseph Hilbe,Mitchell Goldstein,Thomas Hill,Robert Nisbet,Nephi Walton,Gary Miner
  • Publisher : Academic Press
  • Release : 27 September 2014
GET THIS BOOKPractical Predictive Analytics and Decisioning Systems for Medicine

With the advent of electronic medical records years ago and the increasing capabilities of computers, our healthcare systems are sitting on growing mountains of data. Not only does the data grow from patient volume but the type of data we store is also growing exponentially. Practical Predictive Analytics and Decisioning Systems for Medicine provides research tools to analyze these large amounts of data and addresses some of the most pressing issues and challenges where data integrity is compromised: patient safety,

Mining the Social Web

Mining the Social Web
  • Author : Matthew A. Russell,Mikhail Klassen
  • Publisher : O'Reilly Media
  • Release : 04 December 2018
GET THIS BOOKMining the Social Web

Mine the rich data tucked away in popular social websites such as Twitter, Facebook, LinkedIn, and Instagram. With the third edition of this popular guide, data scientists, analysts, and programmers will learn how to glean insights from social media—including who’s connecting with whom, what they’re talking about, and where they’re located—using Python code examples, Jupyter notebooks, or Docker containers. In part one, each standalone chapter focuses on one aspect of the social landscape, including each

Text Mining with R

Text Mining with R
  • Author : Julia Silge,David Robinson
  • Publisher : "O'Reilly Media, Inc."
  • Release : 12 June 2017
GET THIS BOOKText Mining with R

Much of the data available today is unstructured and text-heavy, making it challenging for analysts to apply their usual data wrangling and visualization tools. With this practical book, you’ll explore text-mining techniques with tidytext, a package that authors Julia Silge and David Robinson developed using the tidy principles behind R packages like ggraph and dplyr. You’ll learn how tidytext and other tidy tools in R can make text analysis easier and more effective. The authors demonstrate how treating

Practical Text Analytics

Practical Text Analytics
  • Author : Steven Struhl
  • Publisher : Kogan Page Publishers
  • Release : 03 July 2015
GET THIS BOOKPractical Text Analytics

In an age where customer opinion and feedback can have an immediate, major effect upon the success of a business or organization, marketers must have the ability to analyze unstructured data in everything from social media and internet reviews to customer surveys and phone logs. Practical Text Analytics is an essential daily reference resource, providing real-world guidance on the effective application of text analytics. The book presents the analysis process so that it is immediately understood by the marketing professionals

Data Mining and Predictive Analysis

Data Mining and Predictive Analysis
  • Author : Colleen McCue
  • Publisher : Butterworth-Heinemann
  • Release : 30 December 2014
GET THIS BOOKData Mining and Predictive Analysis

Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis, 2nd Edition, describes clearly and simply how crime clusters and other intelligence can be used to deploy security resources most effectively. Rather than being reactive, security agencies can anticipate and prevent crime through the appropriate application of data mining and the use of standard computer programs. Data Mining and Predictive Analysis offers a clear, practical starting point for professionals who need to use data mining in homeland security, security analysis,

Ensemble Methods in Data Mining

Ensemble Methods in Data Mining
  • Author : Giovanni Seni,John Elder
  • Publisher : Morgan & Claypool Publishers
  • Release : 07 July 2010
GET THIS BOOKEnsemble Methods in Data Mining

Ensemble methods have been called the most influential development in Data Mining and Machine Learning in the past decade. They combine multiple models into one usually more accurate than the best of its components. Ensembles can provide a critical boost to industrial challenges -- from investment timing to drug discovery, and fraud detection to recommendation systems -- where predictive accuracy is more vital than model interpretability. Ensembles are useful with all modeling algorithms, but this book focuses on decision trees

Real-World Data Mining

Real-World Data Mining
  • Author : Dursun Delen
  • Publisher : FT Press
  • Release : 16 December 2014
GET THIS BOOKReal-World Data Mining

Use the latest data mining best practices to enable timely, actionable, evidence-based decision making throughout your organization! Real-World Data Mining demystifies current best practices, showing how to use data mining to uncover hidden patterns and correlations, and leverage these to improve all aspects of business performance. Drawing on extensive experience as a researcher, practitioner, and instructor, Dr. Dursun Delen delivers an optimal balance of concepts, techniques and applications. Without compromising either simplicity or clarity, he provides enough technical depth to

Data Mining and Statistical Analysis Using SQL

Data Mining and Statistical Analysis Using SQL
  • Author : John Lovett,Robert P. Trueblood
  • Publisher : Apress
  • Release : 01 January 2008
GET THIS BOOKData Mining and Statistical Analysis Using SQL

This book is not just another theoretical text on statistics or data mining. Instead, it's designed for database administrators who want to buttress their understanding of statistics to support data mining and customer relationship management analytics and who want to use Structured Query Language (SQL). Each chapter is independent and self-contained with examples tailored to business applications. Each analysis technique is expressed in a mathematical format that lends itself to coding either as a database query or as a Visual

An Introduction to Text Mining

An Introduction to Text Mining
  • Author : Gabe Ignatow,Rada Mihalcea
  • Publisher : SAGE Publications
  • Release : 22 September 2017
GET THIS BOOKAn Introduction to Text Mining

This is the ideal introduction for students seeking to collect and analyze textual data from online sources. It covers the most critical issues that they must take into consideration at all stages of their research projects.