Text Summarization using the TextRank Algorithm in Python

Sections:

Abstract:

Introduction

Why Automatic Text Summarization is Needed

Introduction
Introduction

Automatic Text Summarization is one of the most challenging and interesting problems in the field of Natural Language Processing (NLP).

It is a process of generating a concise and meaningful summary of text from multiple text resources such as emails, news articles, books,  blog posts, research papers, and tweets.

Why Automatic Text Summarization is Needed
Why Automatic Text Summarization is Needed

There are many reasons why Automatic Text Summarization is useful:

  1. Summaries reduce reading time.
  2. When researching documents, summaries make the selection process easier.
  3. Automatic summarization improves the effectiveness of indexing.
  4. Automatic summarization algorithms are less biased than human summarizers.
  5. Personalized summaries are useful in question-answering systems as they provide personalized information.
  6. Using automatic or semi-automatic summarization systems enables commercial abstract services to increase the number of text documents they are able to process.

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