In general terms, the authors typically provide verbose descriptions of the reasons behind the design of specific techniques, with numerical examples and illustrative figures from the slides of two massive open online courses (MOOCs) offered by the first author on Coursera. They also provide specific sections that describe in detail the proper way to evaluate every different kind of technique, a key factor to be taken into account when applying the discussed techniques in practice.
The book, however, is not always self-contained, since its broad scope in a limited number of pages entails an unavoidable depth/breadth tradeoff. Most basic techniques can be implemented just by following the instructions and guidelines in the text, although interested readers might need to resort to the bibliographic references if they want to gain a thorough understanding of the many advanced techniques. Fortunately, the authors include some bibliographic notes and very selective suggestions for further reading at the end of each chapter, instead of the encyclopedic collection of references common in many other textbooks.
Although readers will not find detailed coverage of NLP techniques and some chapters might seem lacking in depth, advanced undergraduate students might find this book to be a valuable reference for getting acquainted with both information retrieval and text mining in a single volume, a worthwhile achievement for a 500-page textbook.