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Java for Data Science

You're reading from   Java for Data Science Examine the techniques and Java tools supporting the growing field of data science

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Product type Paperback
Published in Jan 2017
Publisher Packt
ISBN-13 9781785280115
Length 386 pages
Edition 1st Edition
Languages
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Authors (2):
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Jennifer L. Reese Jennifer L. Reese
Author Profile Icon Jennifer L. Reese
Jennifer L. Reese
Richard M. Reese Richard M. Reese
Author Profile Icon Richard M. Reese
Richard M. Reese
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Table of Contents (13) Chapters Close

Preface 1. Getting Started with Data Science 2. Data Acquisition FREE CHAPTER 3. Data Cleaning 4. Data Visualization 5. Statistical Data Analysis Techniques 6. Machine Learning 7. Neural Networks 8. Deep Learning 9. Text Analysis 10. Visual and Audio Analysis 11. Mathematical and Parallel Techniques for Data Analysis 12. Bringing It All Together

Extracting relationships from sentences

Knowing the relationship between elements of a sentence is important in many analysis tasks. It is useful for assessing the important content of a sentence and providing insight into the meaning of a sentence. This type of analysis has been used for tasks ranging from grammar checking to speech recognition to language translations.

In the previous section, we demonstrated one approach used to extract the parts of speech. Using this technique, we were able to identify the sentence element types present in a sentence. However, the relationships between these elements is missing. We need to parse the sentence to extract these relationships between sentence elements.

Using OpenNLP to extract relationships

There are several techniques and APIs that can be used to extract this type of information. In this section we will use OpenNLP to demonstrate one way of extracting the structure of a sentence. The demonstration is centered around the ParserTool class...

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