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Bhatia AshishSingh - Natural Language Processing with Java: Techniques for Building Machine Learning and Neural Network Models for NLP

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Natural Language Processing with Java will explore how to automatically organize text using approaches such as full-text search, proper name recognition, clustering, tagging, information extraction, and summarization. You will leverage the power of Java to extract relationships within different elements of text and documents.;Cover; Title Page; Copyright and Credits; Dedication; Packt Upsell; Contributors; Table of Contents; Preface; Chapter 1: Introduction to NLP; What is NLP?; Why use NLP?; Why is NLP so hard?; Survey of NLP tools; Apache OpenNLP; Stanford NLP; LingPipe; GATE; UIMA; Apache Lucene Core; Deep learning for Java; Overview of text-processing tasks; Finding parts of text; Finding sentences; Feature-engineering; Finding people and things; Detecting parts of speech; Classifying text and documents; Extracting relationships; Using combined approaches; Understanding NLP models; Identifying the task.

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Natural Language Processing with Java Second Edition Techniques for - photo 1
Natural Language Processing with Java
Second Edition
Techniques for building machine learning and neural network models for NLP
Richard M. Reese
AshishSingh Bhatia

BIRMINGHAM - MUMBAI Natural Language Processing with JavaSecond Edition - photo 2

BIRMINGHAM - MUMBAI
Natural Language Processing with JavaSecond Edition

Copyright 2018 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

Commissioning Editor: Pravin Dhandre
Acquisition Editor: Divya Poojari
Content Development Editor: Eisha Dsouza
Technical Editor: Jovita Alva
Copy Editor: Safis Editing
Project Coordinator: Nidhi Joshi
Proofreader: Safis Editing
Indexer: Tejal Daruwale Soni
Graphics: Jisha Chirayil
Production Coordinator: Shraddha Falebhai

First published: March 2015
Second edition: July 2018

Production reference: 1300718

Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham
B3 2PB, UK.

ISBN 978-1-78899-349-4

www.packtpub.com


To my parents, Smt. Ravindrakaur Bhatia and S. Tej Singh Bhatia, and to my brother, S. Ajit Singh Bhatia, for guiding, motivating, and supporting me when it was required most. To my friends, who are always there, and especially to Mr. Mitesh Soni, for the support and inspiration to write.
AshishSingh Bhatia
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About the authors

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. Richard has written several Java books and a C Pointer book. He uses a concise and easy-to-follow approach to teaching about topics. His Java books have addressed EJB 3.1, updates to Java 7 and 8, certification, functional programming, jMonkeyEngine, and natural language processing.

AshishSingh Bhatia is a learner, reader, seeker, and developer at core. He has over 10 years of IT experience in different domains, including banking, ERP, and education. He is persistently passionate about Python, Java, R, and web and mobile development. He is always ready to explore new technologies.

I would like to first and foremost thank my loving parents and friends for their continued support, patience, and encouragement.
About the reviewers

Doug Ortiz is an experienced enterprise cloud, big data, data analytics, and solutions architect who has designed, developed, re-engineered, and integrated enterprise solutions. His other expertise is in Amazon Web Services, Azure, Google Cloud, business intelligence, Hadoop, Spark, NoSQL databases, and SharePoint, to mention just a few.

He is the founder of Illustris, LLC, and is reachable at dougortiz@illustris.org.

Huge thanks to my wonderful wife, Milla, as well as Maria, Nikolay, and our children for all their support.

Paraskevas V. Lekeas received his PhD and MS in CS from the NTUA, Greece, where he conducted his postdoc on algorithmic engineering, and he also holds degrees in math and physics from the University of Athens. He was a professor at the TEI of Athens and the University of Crete before taking an internship at the University of Chicago. He has extensive experience in knowledge discovery and engineering, having addressed many challenges for startups and for corporations using a diverse arsenal of tools and technologies. He is leading the data group at H5, helping H5 advancing in innovative knowledge discovery.

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Preface

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, Mallet, and more. You'll then start performing NLP on different inputs and tasks, such as tokenization, model training, parts of speech, parsing trees, and more. You'll learn about statistical machine translation, summarization, dialog systems, complex searches, supervised and unsupervised NLP, and other things.

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