Understanding and utilizing your text better with R About This Book * Learn some of the widely used R packages such as Snowball, Tm, plyr, ggplot2 to perform various complexities in the text mining process. * Hands-on recipes to implement real-world case studies and practical examples to illustrate text mining techniques. * Develop your skills by an in-depth understanding of text mining process using R with this easy-to-follow guide. Who This Book Is For This book is intended for anyone who wants to learn about text mining using R. This book provides hands-on recipes explaining pain points faced in text mining which will give you solutions to most common and not-so-common text mining problems. You will need some knowledge of R programming language to understand the flow of the book. What You Will Learn * Discovering Syntagmatic Relation * Analysing Word Association Mining * Implementing of text mining package in R * Quantitatifying discourse analysis of transcripts * Applying textmining using Rattle GUI * Handling white spaces * Implementation of text mining using Big data In Detail The most natural form of storing information is text. Text mining, also known as text data mining or text analytics, refers to the process of extracting interesting and hidden patterns from text documents. R provides an extensive ecosystem with the help of their widely used packages like Snowball, Tm, plyr, ggplot2 and many more. R Text Mining Cookbook will take you through all the required text mining concepts, statistics, tools, how to set up them, algorithms and their implementations in real world. You will be made familiar to work with text data of different complexities. This book will address text mining pain points such as -- working with unstructured or fuzzy data,solving semantic issues, entity recognition with the help of independent and insightful recipes. By the end of this book you will be able to mine text data by implementing set of tasks covered in our easy-to-follow recipes.