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Natural Language Processing Fundamentals

You're reading from   Natural Language Processing Fundamentals Build intelligent applications that can interpret the human language to deliver impactful results

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Product type Paperback
Published in Mar 2019
Publisher
ISBN-13 9781789954043
Length 374 pages
Edition 1st Edition
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Authors (2):
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Dwight Gunning Dwight Gunning
Author Profile Icon Dwight Gunning
Dwight Gunning
Sohom Ghosh Sohom Ghosh
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Sohom Ghosh
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Table of Contents (10) Chapters Close

Preface 1. Introduction to Natural Language Processing FREE CHAPTER 2. Basic Feature Extraction Methods 3. Developing a Text classifier 4. Collecting Text Data from the Web 5. Topic Modeling 6. Text Summarization and Text Generation 7. Vector Representation 8. Sentiment Analysis Appendix

Summarizing Text Using Word Frequency

One of the simplest ways to do text summarization is to compute the frequency of words and extract sentences that contain the words that are most common in the text. This follows a certain process, which is discussed here:

  1. Ignore stop words: Common words (known as stop words) are ignored.
  2. Determine top words: The most frequently occurring words in the document are counted up.
  3. Select top words: A small number of the top words are selected to be used for scoring.
  4. Select top sentences: Sentences are scored on the basis of the total number of the top words they contain. The top four sentences are selected for the summary.

In the next section, we will go through an exercise to get a better understanding of this concept.

Exercise 52: Word Frequency Text Summarization

In this exercise, we will implement text summarization by ranking the sentences using word frequency. Follow these steps to implement this exercise:

    ...
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