Natural language processing for online applications text retrieval extraction and categorization 1st Edition by Peter Jackson, Isabelle Moulinier 9027249881 978-9027249883

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ISBN 10: 9027249881

ISBN 13: 978-9027249883

Author: Peter Jackson, Isabelle Moulinier

This text covers the emerging technologies of document retrieval, information extraction, and text categorization in a way which highlights commonalities in terms of both general principles and practical issues. It seeks to satisfy a need on the part of technology practitioners in the Internet space, faced with having to make difficult decisions as to what research has been done an what the best practices are. It is not intended as a vendor guide (such things are quickly out of date), or as a recipe for building applications (such recipes are very context-dependent). But it does identify the key technologies, the issues involved, and the strengths and weaknesses on evaluation in every chapter, both in terms of methodology (how to evaluate) and what controlled experimentation and industrial experience have to tell us.

Natural language processing for online applications text retrieval extraction and categorization 1st Table of contents:

Chapter 1. Natural Language Processing
1.1 What is NLP?
1.2 NLP and Linguistics
1.3 Linguistic Tools
1.4 Plan of the Book

Chapter 2. Document Retrieval
2.1 Information Retrieval
2.2 Indexing Technology
2.3 Query Processing
2.4 Evaluating Search Engines
2.5 Enhancing Search Performance
2.6 The Future of Web Searching

Chapter 3. Information Extraction
3.1 The Message Understanding Conferences
3.2 Regular Expressions
3.3 Finite Automata in FASTUS
3.4 Context-Free Grammars
3.5 Limitations of Current Technology and Future Directions
3.6 Summary

Chapter 4. Text Categorization
4.1 Overview of Categorization Tasks
4.2 Handcrafted Rule-Based Methods
4.3 Inductive Learning for Text Classification
4.4 Nearest Neighbor Algorithms
4.5 Combining Classifiers
4.6 Evaluating Text Categorization Systems

Chapter 5. Text Mining
5.1 What is Text Mining?
5.2 Resolving Reference and Coreference
5.3 Automatic Summarization
5.4 Testing Automatic Summarization Programs
5.5 Prospects for Text Mining and NLP

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