Angielski
This book explores the process of text analytics in order to increase the accessibility of information available in unstructured text data. Unlike other books available in the text analytics field, Practical Text Analytics opens the door to business analysts and practitioners that may not have extensive coding experience or knowledge of the area. This allows readers without a programming background to take advantage of the nearly limitless information currently shrouded by text. Text analytics can help organizations derive insights for their business from text-based content like emails, documents, or social media posts. This book covers the elements involved in creating a text-mining pipeline. While analysts will not use every element in every project, each tool provides a potential segment in the final pipeline. Understanding the options is key to choosing the appropriate elements in designing and conducting text analysis. Practical Text Analytics: Maximizing the Value of Text Data is divided into five sections. The first section provides an overview of the text analytics process by introducing text analytics, discussing the relationship with content analysis, and providing a general overview of the process. The next section moves on to the actual practice of text analytics, beginning with planning the project. The following section covers the methods of data preparation and pre-processing. Once the data is prepared, the book describes the array of analysis options. The section concludes with a discussion about reporting options, indicating the benefits of various choices for convincing others about the value of the analysis. The last section of the book demonstrates the use of various software programs and programming languages for text analytics. With the practical examples in this book, readers should be able to use these to mine their own text data to uncover hidden information.
