This is the second edition of Nitkin Indurkhya and Fred Damerau's guide to natural language processing (NLP). Damerau passed away before this edition was published, but his contributions are present and acknowledged throughout. Like the first edition, this volume has a practical focus and is targeted at language-engineering professionals. Its stated goals are to focus on practical tools and techniques and discuss NLP as it pertains to input to and output from computer systems. The second edition includes greater coverage of NLP in non-English languages and has a companion wiki with post-publication content and links to useful online resources.The handbook is organized into three sections. The first, Classical Approaches, covers historical and foundational roots of the field. Its chapters introduce techniques for organizing text data, parsing it into words and other meaningful units, and conducting basic syntactic and semantic analyses. A final chapter introduces language generation. The second section presents modern empirical/statistical NLP. It divides the territory as linguists would expect. Separate chapters cover creation and management of large samples of language, statistical techniques, parsing and part-of-speech tagging, word sense disambiguation, and speech recognition and translation. The third selection examines some representative NLP applications, including machine translation, question answering, and text mining.The book presents a great deal of densely-technical information in a fairly readable manner. (The statistics chapter is an exception; it could use additional detail and a less theory-driven emphasis.) It is not intended as a textbook, so the reader shouldn't expect much hand-holding. Nor is the coverage of topics comprehensive. But there are numerous useful references in the text and links in the book's wiki to more detailed sources. Although there are no exercises per se, the example procedures are presented well. It is a useful handbook and reference that is comparable to--and updates--Manning and Schuetze's Foundations of Statistical Natural Language Processing.So check it out of the library and give it a skim. If you are working in this area, consider obtaining your own mark-up-able desk copy.