Blueprints for Text Analytics Using Python

Chapter 9. Text Summarization

There is a massive amount of information on the internet on every topic. A Google search returns millions of search results containing text, images, videos, and so on. Even if we consider only the text content, it’s not possible to read through it all. Text summarization methods are able to condense text information to a short summary of a few lines or a paragraph and make it digestible to most users. Applications of text summarization can be found not just on the internet but also in fields like paralegal case summaries, book synopses, etc.

What You’ll Learn and What We’ll Build

In this chapter, we will start with an introduction to text summarization and provide an overview of the methods used. We will analyze different types of text data and their specific characteristics that are useful in determining the choice of summarization method. We will provide blueprints that apply these methods to different use cases and analyze their performance. At the end of this chapter, you will have a good understanding of different text summarization methods and be able to choose the right approach for any application.

Text Summarization

It is likely that you have undertaken a summarization task knowingly or unknowingly at some point in life. Examples are telling a friend about a movie you watched last night and trying to explain your work to your family. We all like to provide a brief summary of our experiences to the rest of the world to share our feelings ...