Reading data from diverse sources for analysis, and exporting the results to another system for reporting purposes can be a daunting task that can sometimes take even more time than the real analysis. There are various sources from which we can gather text; some of them are HTML pages, social media, RSS feeds, JSON or XML, enterprise environments, and so on. The source has a very important role to play in the quality of textual data and the way we access the source. For instance, in the case of an enterprise environment, the common sources of text or data can be database and log files. In a web ecosystem, web pages are the source of data. When we consider web service applications, the sources can be JSON or XML over HTTP or HTTPS. We will look into various data sources and ways in which we can collect data from them.
Mastering Text Mining with R
By :
Mastering Text Mining with R
By:
Overview of this book
Text Mining (or text data mining or text analytics) is the process of extracting useful and high-quality information from text by devising patterns and trends. R provides an extensive ecosystem to mine text through its many frameworks and packages.
Starting with basic information about the statistics concepts used in text mining, this book will teach you how to access, cleanse, and process text using the R language and will equip you with the tools and the associated knowledge about different tagging, chunking, and entailment approaches and their usage in natural language processing. Moving on, this book will teach you different dimensionality reduction techniques and their implementation in R. Next, we will cover pattern recognition in text data utilizing classification mechanisms, perform entity recognition, and develop an ontology learning framework.
By the end of the book, you will develop a practical application from the concepts learned, and will understand how text mining can be leveraged to analyze the massively available data on social media.
Table of Contents (15 chapters)
Mastering Text Mining with R
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Free Chapter
Statistical Linguistics with R
Processing Text
Categorizing and Tagging Text
Dimensionality Reduction
Text Summarization and Clustering
Text Classification
Entity Recognition
Index
Customer Reviews