Book Image

Natural Language Processing with Java - Second Edition

By : Richard M. Reese
Book Image

Natural Language Processing with Java - Second Edition

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 (19 chapters)
Title Page
Dedication
Packt Upsell
Contributors
Preface
Index

Boolean retrieval


Boolean retrieval deals with a retrieval system or algorithm where the IR query can be seen as a Boolean expression of terms using the operations AND, OR, and NOT. A Boolean retrieval model is a model that sees the document as words and can apply query terms using Boolean expressions. A standard example is to consider Shakespeare's collected works. The query is to determine plays that contain the words "Brutus" and "Caesar," but not "Calpurnia." Such a query is feasible using the grep command which is available on Unix-based systems.

It is an effective process when the document size is limited, but to process a large a document quickly, or the amount of data available on the web, and rank it on the basis of an occurrence count, is not possible.

The alternative is to index the document in advance for the terms. The approach is to create an incidence matrix, which records in a form of binary and marks whether the term is present in the given play or not:

Antony and Cleopatra...