Automatic Text Summarization

Authors

  • Harshit Garg Student, Department of Computer Science & Engineering, Global Institute of Technology Jaipur, Rajasthan, India
  • Harshit Vijayvergiya Student, Department of Computer Science & Engineering Global Institute of Technology, Jaipur, Rajasthan, India
  • Anidhya Athaiya Assistant Professor Department of Computer Science & Engineering Global Institute of Technology, Jaipur, Rajasthan,India

Keywords:

Text summarization, Extractive summary, abstractive summary, data extraction, novel sentences etc.

Abstract

The amount of data available to us both online and offline is growing extremely and due to this summarization became increasingly important
over the past few years. Automatic Summarization is the process of reducing a document to a small document called summary that contains
the significant or key points of the original document. Automatic Text Summarization is broadly classified into two categories i.e Extractive Summarization and Abstractive Summarization. Extractive Summary is a subset of the original document that represents important data contained in the document. An abstractive summary may contain some novel sentences that are not present in the whole document. In this context we are working on extractive summarization where we are including important sentences from the document in the summary with limited length. Automatic summarization is a technique by which the data is extracted and shorten from text document by the use of software .

References

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Published

2020-06-03