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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

What is topic modeling?


In very simple terms, topic modeling is a technique by which the computer programs try and extract a topic from the text. The text is usually unstructured data, such as a blog, email, article, a chapter from a book, or something similar. It is a text-mining approach, but should not be confused with rule-based text mining. In a machine learning scenario, topic modeling falls under the category of unsupervised learning, where the machine or computer program tries to find the topic by observing a bunch of words in the last collection of text. A good model should result in the words "program", "programmer", "IT", "computer", "software", and "hardware" when given the topic of "IT industry". It helps in making sense of large text, and plays a vital role in the operation of search engines.

Topic modeling can be used with methods to organize, categorize, understand, and summarize large collections of textual information. It enables us to discover hidden patterns in collections...

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