AI-Saransh - Document Summarization
It is a technique that shortens a long piece of content with main points outlined that gives an idea of the whole content. It becomes critical when someone needs a quick and accurate summary of very long content. Summarizing text can be expensive and time-consuming if done manually. Machine learning and natural processing language are helpful in creating an automatic text summary.
Types of Document Summarization-
Extractive Summarization:
Extractive text summarization is an algorithm that extracts the text from the original content without making any changes in it on the basis of a defined metric. It is generally based on the weight of the essential section of text or words and their rephrasing. Different types of methods could be used to measure the weight of the sentences.
Abstractive Summarization:
Unlike extractive, abstractive text summarization is more close to humans expectation. The algorithm creates sentences and phrases to express the most useful information from the original text. It avoids the grammar inconsistencies that usually happens in extraction based text summarization.
