Book Image

Natural Language Processing with Java Cookbook

By : Richard M. Reese
Book Image

Natural Language Processing with Java Cookbook

By: Richard M. Reese

Overview of this book

Natural Language Processing (NLP) has become one of the prime technologies for processing very large amounts of unstructured data from disparate information sources. This book includes a wide set of recipes and quick methods that solve challenges in text syntax, semantics, and speech tasks. At the beginning of the book, you'll learn important NLP techniques, such as identifying parts of speech, tagging words, and analyzing word semantics. You will learn how to perform lexical analysis and use machine learning techniques to speed up NLP operations. With independent recipes, you will explore techniques for customizing your existing NLP engines/models using Java libraries such as OpenNLP and the Stanford NLP library. You will also learn how to use NLP processing features from cloud-based sources, including Google and Amazon Web Services (AWS). You will master core tasks, such as stemming, lemmatization, part-of-speech tagging, and named entity recognition. You will also learn about sentiment analysis, semantic text similarity, language identification, machine translation, and text summarization. By the end of this book, you will be ready to become a professional NLP expert using a problem-solution approach to analyze any sort of text, sentence, or semantic word.
Table of Contents (14 chapters)

Isolating Sentences within a Document

The process of extracting sentences from text is known as Sentence Boundary Disambiguation (SBD). While this process may initially appear to be simple, there are many complicating factors that ultimately demand more sophisticated approaches, such as using neural networks.

The end of a sentence is typically marked with a period. However, there are other terminators used, such as question marks and exclamation marks. If these were the only considerations, then the process would be easy. However, even limiting the problem to periods, we find that periods are used in many places including abbreviations, numbers, and ellipses. A sentence might use periods such as Mr. Smith, 2.005, or 3.12.18. Ellipses may be simply three periods back, to back or a Unicode character might be used.

Specialized text such as scientific text may contain unusual uses...