Natural Language Processing with Java Cookbook
eBook - ePub

Natural Language Processing with Java Cookbook

Over 70 recipes to create linguistic and language translation applications using Java libraries

Richard M. Reese

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  1. 386 páginas
  2. English
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eBook - ePub

Natural Language Processing with Java Cookbook

Over 70 recipes to create linguistic and language translation applications using Java libraries

Richard M. Reese

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Información del libro

A problem-solution guide to encounter various NLP tasks utilizing Java open source libraries and cloud-based solutions

Key Features

  • Perform simple-to-complex NLP text processing tasks using modern Java libraries Extract relationships between different text complexities using a problem-solution approach
  • Utilize cloud-based APIs to perform machine translation operations

Book Description

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's 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, sentences, or semantic words.

What you will learn

  • Explore how to use tokenizers in NLP processing
  • Implement NLP techniques in machine learning and deep learning applications
  • Identify sentences within the text and learn how to train specialized NER models
  • Learn how to classify documents and perform sentiment analysis
  • Find semantic similarities between text elements and extract text from a variety of sources
  • Preprocess text from a variety of data sources
  • Learn how to identify and translate languages

Who this book is for

This book is for data scientists, NLP engineers, and machine learning developers who want to perform their work on linguistic applications faster with the use of popular libraries on JVM machines. This book will help you build real-world NLP applications using a recipe-based approach. Prior knowledge of Natural Language Processing basics and Java programming is expected.

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Información

Año
2019
ISBN
9781789808834

Contributors

About the author

Richard M. Reese has worked in both industry and academia. For 17 years, he worked in the telephone and aerospace industries, serving in several capacities, including research and development, software development, supervision, and training. He currently teaches at Tarleton State University, where he has the opportunity to apply his years of industry experience to enhance his teaching. Richard has written several Java books and a C pointer book. He uses a concise and easy-to-follow approach to the topics at hand. His Java books have addressed EJB 3.1, updates to Java 7 and 8, certification, jMonkeyEngine, natural language processing, functional programming, networks, and data science.

About the reviewer

Jennifer L. Reese studied computer science at Tarleton State University. She also earned her M.Ed. from Tarleton in December 2016. She currently teaches computer science to high-school students. Her interests include the integration of computer science concepts with other academic disciplines, increasing diversity in computer science courses, and the application of data science to the field of education. She has co-authored two books: Java for Data Science, and Java 7 New Features Cookbook. She previously worked as a software engineer. In her fre...

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