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.
General
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