Book Image

Natural Language Processing Fundamentals

By : Sohom Ghosh, Dwight Gunning
Book Image

Natural Language Processing Fundamentals

By: Sohom Ghosh, Dwight Gunning

Overview of this book

If NLP hasn't been your forte, Natural Language Processing Fundamentals will make sure you set off to a steady start. This comprehensive guide will show you how to effectively use Python libraries and NLP concepts to solve various problems. You'll be introduced to natural language processing and its applications through examples and exercises. This will be followed by an introduction to the initial stages of solving a problem, which includes problem definition, getting text data, and preparing it for modeling. With exposure to concepts like advanced natural language processing algorithms and visualization techniques, you'll learn how to create applications that can extract information from unstructured data and present it as impactful visuals. Although you will continue to learn NLP-based techniques, the focus will gradually shift to developing useful applications. In these sections, you'll understand how to apply NLP techniques to answer questions as can be used in chatbots. By the end of this book, you'll be able to accomplish a varied range of assignments ranging from identifying the most suitable type of NLP task for solving a problem to using a tool like spacy or gensim for performing sentiment analysis. The book will easily equip you with the knowledge you need to build applications that interpret human language.
Table of Contents (10 chapters)

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:

    ...