Text Summarization
Automated text summarization is the process of using NLP tools to produce concise versions of text that preserve the key information present in the original content. Good summaries can communicate the content with less text by retaining the key information while filtering out other information and noise (or useless text, if any). A shorter text may often take less time to read, and thus summarization facilitates more efficient use of time.
The type of summarization that we are typically taught in school is abstractive summarization. One way to think of this is to consider abstractive summarization as a combination of understanding the meaning and expressing it in fewer sentences. It is usually considered as a supervised learning problem as the original text and the summary are both required. However, a piece of text can be summarized in more than one way. This makes it hard to teach the machine in a general way. While abstractive summarization is an active area...
