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Natural Language Processing with Java

Natural Language Processing with Java - Second Edition

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

Natural Language Processing with Java

2 (3)
By: Richard M. Reese, AshishSingh Bhatia

Overview of this book

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, 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.
Table of Contents (14 chapters)
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Understanding sentiment analysis


With sentiment analysis, we are concerned with who holds what type of feeling about a specific product or topic. This can tell us, for example, that citizens of a particular city hold positive or negative feelings about the performance of a sports team. They may hold a different sentiment about the team's performance than they do about its management.

Sentiment analysis can be useful in automatically determining the sentiment regarding certain aspects, or attributes, of a product and then displaying the results in some meaningful manner.

This is illustrated using a review of the 2014 Camry from the Kelly Blue Book (http://www.kbb.com/toyota/camry/2014-toyota-camry/?r=471659652516861060), as shown in the following screenshot:

If you scroll down you can find the expert review about the model shown as following:

The attributes, such as the overall rating and value, are depicted both as a bar graph and as a numeric value. The calculation of these values can be performed...

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