
Natural Language Processing with Java
Techniques for building machine learning and neural network models for NLP
Packt Publishing
2nd Edition
Published on 31. July 2018
Book
Paperback/Softback
318 pages
978-1-78899-349-4 (ISBN)
Description
Explore various approaches to organize and extract useful text from unstructured data using Java
Key Features
Use deep learning and NLP techniques in Java to discover hidden insights in text
Work with popular Java libraries such as CoreNLP, OpenNLP, and Mallet
Explore machine translation, identifying parts of speech, and topic modeling
Book DescriptionNatural 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.
What you will learn
Understand basic NLP tasks and how they relate to one another
Discover and use the available tokenization engines
Apply search techniques to find people, as well as things, within a document
Construct solutions to identify parts of speech within sentences
Use parsers to extract relationships between elements of a document
Identify topics in a set of documents
Explore topic modeling from a document
Who this book is forNatural Language Processing with Java is for you if you are a data analyst, data scientist, or machine learning engineer who wants to extract information from a language using Java. Knowledge of Java programming is needed, while a basic understanding of statistics will be useful but not mandatory.
Key Features
Use deep learning and NLP techniques in Java to discover hidden insights in text
Work with popular Java libraries such as CoreNLP, OpenNLP, and Mallet
Explore machine translation, identifying parts of speech, and topic modeling
Book DescriptionNatural 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.
What you will learn
Understand basic NLP tasks and how they relate to one another
Discover and use the available tokenization engines
Apply search techniques to find people, as well as things, within a document
Construct solutions to identify parts of speech within sentences
Use parsers to extract relationships between elements of a document
Identify topics in a set of documents
Explore topic modeling from a document
Who this book is forNatural Language Processing with Java is for you if you are a data analyst, data scientist, or machine learning engineer who wants to extract information from a language using Java. Knowledge of Java programming is needed, while a basic understanding of statistics will be useful but not mandatory.
More details
Edition
2nd Revised edition
Language
English
Place of publication
Birmingham
United Kingdom
Target group
Professional and scholarly
US School Grade: College Graduate Student
Edition type
Revised edition
Dimensions
Height: 235 mm
Width: 191 mm
Thickness: 18 mm
Weight
597 gr
ISBN-13
978-1-78899-349-4 (9781788993494)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Richard M. Reese | Ashishsingh Bhatia
Natural Language Processing with Java
Techniques for building machine learning and neural network models for NLP
E-Book
09/2024
2nd Edition
Packt Publishing
€31.49
Available for download
Persons
Richard Reese has worked in the industry and academics for the past 29 years. For 10 years he provided software development support at Lockheed and at one point developed a C based network application. He was a contract instructor providing software training to industry for 5 years. Richard is currently an Associate Professor at Tarleton State University in Stephenville Texas. Richard is the author of various books and video courses some of which are as follows: Natural Language Processing with Java. Java for Data Science Getting Started with Natural Language Processing in Java AshishSingh Bhatia is a reader and learner at his core. He has more than 11 years of rich experience in different IT sectors, encompassing training, development, and management. He has worked in many domains, such as software development, ERP, banking, and training. He is passionate about Python and Java, and recently he has been exploring R. He is mostly involved in web and mobile developments in various capacity. He always likes to explore new technologies and share his views and thoughts through various online medium and magazines. He believes in sharing his experience with new generation and do take active part in training and teaching also.
Content
Table of Contents
Introduction to NLP
Finding Parts of Text
Finding Sentences
Finding People and Things
Detecting Parts of Speech
Representing text with features
Information retrieval
Classifying Texts and Documents
Topic Modeling
Using Parser to Extract Relationships
Combined Pipeline
Creating chat Bot
Introduction to NLP
Finding Parts of Text
Finding Sentences
Finding People and Things
Detecting Parts of Speech
Representing text with features
Information retrieval
Classifying Texts and Documents
Topic Modeling
Using Parser to Extract Relationships
Combined Pipeline
Creating chat Bot