English For Today : For Classes 11-12

Multilingual Natural Language Processing Applications is the first comprehensive single-source guide to building robust and accurate multilingual NLP systems. Edited by two leading experts, it integrates cutting-edge advances with practical solutions drawn from extensive field experience.

Part I introduces the core concepts and theoretical foundations of modern multilingual natural language processing, presenting today’s best practices for understanding word and document structure, analyzing syntax, modeling language, recognizing entailment, and detecting redundancy.

Part II thoroughly addresses the practical considerations associated with building real-world applications, including information extraction, machine translation, information retrieval/search, summarization, question answering, distillation, processing pipelines, and more.

This book contains important new contributions from leading researchers at IBM, Google, Microsoft, Thomson Reuters, BBN, CMU, University of Edinburgh, University of Washington, University of North Texas, and others.

Salient Features
* The first book on multilingual NLP, a crucial technology for global organizations
* Contains new contributions from many of the field's leading researchers
* Combines coverage of core technologies with insights into practical usage and applications
* NLP is one of the core technologies behind IBM's Watson computer, and several of the contributors worked on Watson

About the Author
Daniel M. Bikel is a senior research scientist at Google, developing new methods for NLP and speech recognition. While at IBM, he architected the distillation system for IBM’s GALE multilingual information extraction and question-answering system. While pursuing his doctorate at Penn, he built the first extensible multilingual syntactic parsing engine.

Imed Zitouni is a senior research scientist at IBM. He has led IBM’s Arabic information extraction and data resources efforts since 2004. He previously led both DIALOCA’s Speech/NLP group and Bell Labs/ Alcatel-Lucent’s language modeling and call routing activities. His work involves machine translation, NLP, and spoken dialog systems.

Table of Contents
* Preface
* Acknowledgments
* About the Authors
* Part I: In Theory
* Chapter 1: Finding the Structure of Words
* Chapter 2: Finding the Structure of Documents
* Chapter 3: Syntax
* Chapter 4: Semantic Parsing
* Chapter 5: Language Modeling
* Chapter 6: Recognizing Textual Entailment
* Chapter 7: Multilingual Sentiment and Subjectivity Analysis
* Part II: In Practice
* Chapter 8: Entity Detection and Tracking
* Chapter 9: Relations and Events
* Chapter 10: Machine Translation
* Chapter 11: Multilingual Information Retrieval
* Chapter 12: Multilingual Automatic Summarization
* Chapter 13: Question Answering
* Chapter 14: Distillation
* Chapter 15: Spoken Dialog Systems
* Chapter 16: Combining Natural Language Processing Engines
* Index