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Natural Language Processing with Java

You're reading from   Natural Language Processing with Java Techniques for building machine learning and neural network models for NLP

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Product type Paperback
Published in Jul 2018
Publisher
ISBN-13 9781788993494
Length 318 pages
Edition 2nd Edition
Languages
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Authors (2):
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Ashish Bhatia Ashish Bhatia
Author Profile Icon Ashish Bhatia
Ashish Bhatia
Richard M. Reese Richard M. Reese
Author Profile Icon Richard M. Reese
Richard M. Reese
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Toc

Table of Contents (14) Chapters Close

Preface 1. Introduction to NLP FREE CHAPTER 2. Finding Parts of Text 3. Finding Sentences 4. Finding People and Things 5. Detecting Part of Speech 6. Representing Text with Features 7. Information Retrieval 8. Classifying Texts and Documents 9. Topic Modeling 10. Using Parsers to Extract Relationships 11. Combined Pipeline 12. Creating a Chatbot 13. Other Books You May Enjoy

Summary

In this chapter, we illustrated various approaches to tokenizing text and performing normalization on text. We started with simple tokenization techniques based on core Java classes, such as the String class' split method and the StringTokenizer class. These approaches can be useful when we decide to forgo the use of the NLP API classes.

We demonstrated how tokenization can be performed using the OpenNLP, Stanford, and LingPipe APIs. We found variations in how tokenization can be performed andĀ options that can be applied in these APIs. A brief comparison of their output was provided.

Normalization was discussed, which can involve converting characters to lowercase, expanding abbreviations, removing stopwords, stemming, and lemmatization. We illustrated how these techniques can be applied using both core Java classes and the NLP APIs.

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