artificial intelligence

Allen's book is a standard introduction to NLP in industry and academia. His exposition permits straightforward implementation and provides a lucid motivation for the algorithms he describes. "Natural Language Understanding" was the first NLP text I read (for a summer job), and I've always referred to it first for its balance of formal and practical considerations.

However, some developments in the past few years outpace his treatment. In particular, the stochastic viewpoint has become more common in natural-language processing, and Allen does not consider related innovations in great depth. Passing mention of the interaction between NLP and the speech processing and information retrievals would also benefit a revised version.

James Allen introduces the concepts required to build a NL system without losing you in the psycholinguistics, psychology and philosophy of language. The great part is that he gives you enough of a background in each of these fields before going into a topic in depth. Plenty of examples help define words like "morpheme" so you don't get lost in the psychobabble jargon of the required disciplines. (Wouldn't that be an ironic thing to have happen in a NLP book?!) :)

I'd love to tell you more, but I only stopped by to catch the author's name and look for whitepapers on his (hopefully existant) website.

This books serves as a very useful introduction to computational linguistics. It is clearly laid out, and will serve the reader for many years as a continuing reference.

The TRAINS project at Rochester (the author's institution) was based on many of the concepts outlined in this book... proof that they work and can be made to handle real-world situations.

I continue to use it, now in its second edition as a reference for myself, and to train those who need to work with our project.

I cannot recommend a book more highly. If you want to learn computational linguistics, or need to push the state of the art, this is the book you need.