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Natural Language Processing with Java

You're reading from   Natural Language Processing with Java Techniques for building machine learning and neural network models for NLP

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Product type Paperback
Published in Jul 2018
Publisher
ISBN-13 9781788993494
Length 318 pages
Edition 2nd Edition
Languages
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Authors (2):
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Ashish Bhatia Ashish Bhatia
Author Profile Icon Ashish Bhatia
Ashish Bhatia
Richard M. Reese Richard M. Reese
Author Profile Icon Richard M. Reese
Richard M. Reese
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Toc

Table of Contents (14) Chapters Close

Preface 1. Introduction to NLP FREE CHAPTER 2. Finding Parts of Text 3. Finding Sentences 4. Finding People and Things 5. Detecting Part of Speech 6. Representing Text with Features 7. Information Retrieval 8. Classifying Texts and Documents 9. Topic Modeling 10. Using Parsers to Extract Relationships 11. Combined Pipeline 12. Creating a Chatbot 13. Other Books You May Enjoy

Topic modeling with MALLET


MALLET is a well-known library in topic modeling. It also supports document classification and sequence tagging. More about MALLET can be found at http://mallet.cs.umass.edu/index.php. To download MALLET, visit http://mallet.cs.umass.edu/download.php (the latest version is 2.0.6). Once downloaded, extract MALLET in the directory. It contains the sample data in .txt format in the sample-data/web/en path of the MALLET directory.

The first step is to import the files into MALLET's internal format. To do this, open the Command Prompt or Terminal, move to the mallet directory, and execute the following command:

mallet-2.0.6$ bin/mallet import-dir --input sample-data/web/en --output tutorial.mallet --keep-sequence --remove-stopwords

This command will generate the tutorial.mallet file.

Training

The next step is to use train-topics to build a topic model and save the output-state, topic-keys, and topics using the train-topics command:

mallet-2.0.6$ bin/mallet train-topics -...
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