Text summarization is the process of condensing larger documents into shorter and precise paragraphs or sentences

Automatic Text Summarization

Automatic text summarization, or just text summarization, is the process of creating a short and coherent version of a longer document.

Two Types of Summarization

There are two main types of Text Summarization

Extractive

This method does not create new words or phrases, it just takes the already existing words and phrases and presents only that. You can imagine this as taking a page of text and marking the most important sentences using a highlighter.

Abstractive

It creates words and phrases, puts them together in a meaningful way, and along with that, adds the most important facts found in the text. This way, abstractive summarization techniques are more complex than extractive summarization techniques and are also computationally more expensive.

Applications of Summarization

• The first is generic summarization, which focuses on obtaining a generic summary or abstract of the collection (whether documents, or sets of images, or videos, news stories etc.).
• The second is query relevant summarization, sometimes called query-based summarization, which summarizes objects specific to a query.
• Image collection summarization
• Video summarization
• Keyphrase Extraction
• Depending on the different literature and the definition of key terms, words or phrases, Document Summarization is a highly related theme

Steps required in Document Summarization

The process of document summarization involves several steps such as:

1. Preprocessing the text