Text Summarization

Learn about the extractive and abstractive summarization techniques for text summarization.

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Types of text summarization
Extractive summarization
Abstractive summarization

Text summarization is the process of converting a long text into its summary. Suppose we have a Wikipedia article and say we don't want to read the whole article—we just need an overview of the article. In this case, summarizing the Wikipedia article will help us get an overview of the article. Text summarization is widely used for a variety of applications, such as summarizing long documents, news articles, and blog posts, to name a few. In the text summarization task, given a long text, our goal is to convert the given long text into its summary as shown in the following figure:

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Before we Start

Starting Off with BERT

A Primer on Transformers

Understanding the BERT Model

Getting Hands-On with BERT

Exploring BERT Variants

Different BERT Variants

BERT Variants—Based on Knowledge Distillation

Applications of BERT

Exploring BERTSUM for Text Summarization

Applying BERT to Other Languages

Exploring Sentence and Domain-Specific BERT

Working with VideoBERT, BART, and More

Conclusion

Text Summarization