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Natural Language Processing with Java

Natural Language Processing with Java

By : Richard M. Reese
2 (3)
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Natural Language Processing with Java

Natural Language Processing with Java

2 (3)
By: Richard M. Reese

Overview of this book

Natural Language Processing (NLP) allows you to take any sentence and identify patterns, special names, company names, and more. The second edition of Natural Language Processing with Java teaches you how to perform language analysis with the help of Java libraries, while constantly gaining insights from the outcomes. You’ll start by understanding how NLP and its various concepts work. Having got to grips with the basics, you’ll explore important tools and libraries in Java for NLP, such as CoreNLP, OpenNLP, Neuroph, and Mallet. You’ll then start performing NLP on different inputs and tasks, such as tokenization, model training, parts-of-speech and parsing trees. You’ll learn about statistical machine translation, summarization, dialog systems, complex searches, supervised and unsupervised NLP, and more. By the end of this book, you’ll have learned more about NLP, neural networks, and various other trained models in Java for enhancing the performance of NLP applications.
Table of Contents (14 chapters)
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Summary

In this chapter, we introduced NLP and its uses. We found that it is used in many places to solve many different types of problems, ranging from simple searches to sophisticated classification problems. The Java support for NLP in terms of core string support and advanced NLP libraries was presented. The basic NLP tasks were explained and illustrated using code. The basics of deep learning in NLP and feature-engineering were also included to show how deep learning is impacting NLP. We also examined the process of training, verifying, and using models.

In this book, we will lay the foundation for employing basic NLP tasks using both simple and more complex approaches. You may find that some problems require only simple approaches, and when that is the case, knowing how to use the simple techniques may be more than adequate. In other situations, a more sophisticated technique may be needed. In either case, you will be prepared to identify which tool is needed and be able to choose the appropriate technique for the task.

In the next chapter, Chapter 2, Finding Parts of Text, we will examine the process of tokenization and see how it can be used to find parts of text.

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