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Natural Language Processing with Java Cookbook

Natural Language Processing with Java Cookbook

By : Richard M. Reese, Richard M Reese
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Natural Language Processing with Java Cookbook

Natural Language Processing with Java Cookbook

By: Richard M. Reese, 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)
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Creating, inverting, and using dictionaries

Dictionaries hold key-value pairs where the key is the index. An inverted dictionary is one where the values become the keys and the keys becomes the values. Dictionaries are frequently used to support many NLP tasks. For example, in the previous recipe, Summarizing text in a document, the LinkedHashMap class was used internally to maintain the word frequency with respect to the number of occurrences for text.

In this recipe, we will explore how dictionaries and inverted dictionaries are handled in Java. We will use the Java core SDK and the Guava (Google core libraries for Java and API for our libraries). The Guava website is found at https://github.com/google/guava.

Problems can arise when the values are not unique. We will use the Java 8 Streams to address these issues.
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