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About this Book


Taming Text is about building software applications that derive their core value from using and manipulating content that primarily consists of the written word. This book is not a theoretical treatise on the subjects of search, natural language processing, and machine learning, although we cover all of those topics in a fair amount of detail throughout the book. We strive to avoid jargon and complex math and instead focus on providing the concepts and examples that today’s software engineers, architects, and practitioners need in order to implement intelligent, next-generation, text-driven applications. Taming Text is also firmly grounded in providing real-world examples of the concepts described in the book using freely available, highly popular, open source tools like Apache Solr, Mahout, and OpenNLP.

Who should read this book

Is this book for you? Perhaps. Our target audience is software practitioners who don’t have (much of) a background in search, natural language processing, and machine learning. In fact, our book is aimed at practitioners in a work environment much like what we’ve seen in many companies: a development team is tasked with adding search and other features to a new or existing application and few, if any, of the developers have any experience working with text. They need a good primer on understanding the concepts without being bogged down by the unnecessary.


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