Build effective natural language processing applications
Transit from ad-hoc methods to advanced machine learning techniques
Use advanced techniques such as logistic regression, conditional random fields, and latent Dirichlet allocation

Who This Book Is For
This book is for experienced Java developers with NLP needs, whether academics, industrialists, or hobbyists. A basic knowledge of NLP terminology will be beneficial.

What You Will Learn

Master a broad range of classification techniques for text data
Track people, concepts, and things in data, within and across documents
Understand the importance of evaluation in creation of NLP applications and how to do it
Yield best practices for common text-analytics problems
Tune systems for high performance and trade off various aspects of the performance curve
Become a master in customizing NLP systems at all levels
Build systems for non-tokenized languages such as Chinese and Japanese

In Detail
NLP is at the core of web search, intelligent personal assistants, marketing, and much more, and LingPipe is a toolkit for processing text using computational linguistics.

This book starts with the foundational but powerful techniques of language identification, sentiment classifiers, and evaluation frameworks. It goes on to detail how to build a robust framework to solve common NLP problems, before ending with advanced techniques for complex heterogeneous NLP systems.

This is a recipe and tutorial book for experienced Java developers with NLP needs. A basic knowledge of NLP terminology will be beneficial. This book will guide you through the process of how to build NLP apps with minimal fuss and maximal impact.

About the Author

Breck Baldwin is the Founder and President of Alias-i/LingPipe. The company focuses on system building for customers, education for developers, and occasional forays into pure research. He has been building large-scale NLP systems since 1996. He enjoys telemark skiing and wrote DIY RC Airplanes from Scratch: The Brooklyn Aerodrome Bible for Hacking the Skies, McGraw-Hill/TAB Electronics. Krishna Dayanidhi has spent most of his professional career focusing on Natural Language Processing technologies. He has built diverse systems, from a natural dialog interface for cars to Question Answering systems at (different) Fortune 500 companies. He also confesses to building those automated speech systems for very large telecommunication companies. He's an avid runner and a decent cook.