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Introduction to Topic Modeling and Text Categorization in NLP

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Introduction to Topic Modeling and Text Categorization in NLP

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Questions and Answers

What is the process of recognizing hidden structure in data called?

Unsupervised learning

NLP modeling

Supervised learning

Topic modeling (correct)

Which type of learning is used in text categorization?

NLP modeling

Unsupervised learning

Generative probabilistic model

Supervised learning (correct)

What is the assumption in topic modeling using LDA?

Text features are combined in deep learning models

NLP is the basis of machine intelligence

Categories are predefined

Documents are a combination of different topics (correct)

What technique is commonly used in text classification?

<p>tfidf (C)</p> Signup and view all the answers

What does NLP stand for?

<p>Natural Language Processing (D)</p> Signup and view all the answers

Study Notes

Unsupervised Learning and NLP

The process of recognizing hidden structure in data is called unsupervised learning.

Text Analysis

Text categorization uses supervised learning.
Topic modeling using Latent Dirichlet Allocation (LDA) assumes that each document is a mixture of topics and each topic is a mixture of words.

Techniques in NLP

The commonly used technique in text classification is supervised learning.
NLP stands for Natural Language Processing.

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Description

Explore the fundamentals of Natural Language Processing (NLP) and its applications in topic modeling and text categorization. Learn about unsupervised learning, recognizing hidden structure in data, and generative probabilistic models like LDA.