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Natural Language Processing with Java

Natural Language Processing with Java - Second Edition

By : Richard M. Reese
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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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Finding Sentences

Partitioning text into sentences is also called sentence boundary disambiguation (SBD). This process is useful for many downstream NLP tasks that require analysis within sentences; for example, POS and phrase analysis typically work within a sentence.

In this chapter, we will explain why SBD is difficult. Then, we will examine some core Java approaches that may work in some situations, and move on to the use of models by various NLP APIs. We will also examine training and validating approaches for sentence-detection models. We can add additional rules to refine the process further, but this will work only up to a certain point. After that, models must be trained to handle both common and specialized situations. The latter part of this chapter focuses on these models and their use.

We will cover the following topics in this chapter:

  • The SBD process
  • What makes...
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