Identification and Effective Summary Extraction with Deduplication of Data in News Articles

Authors

  • Rajat Bodankar  M. Tech , Computer Science and Engineering Nagpur, Maharashtra, India
  • Mayuri Waghmare  M. Tech , Computer Science and Engineering Nagpur, Maharashtra, India

DOI:

https://doi.org/10.32628/IJSRSET207620

Keywords:

Multi-Document Summarization, Clustering Based, Extractive and Abstractive approach, Ranked Based, LDA Based, Natural Language Processing.

Abstract

Text summary, which is the most prominent application for data pressure, is provided for natural language processing. Content rundown is a process for the summary of the unique archive measurement by reducing the number of vital data from a uniquely reported report. In less time, a need emerges that the development of information increases greatly on the World Wide Web or on desktops of customers so that the multi-document overview is the best way of summarising it in less time. This paper presents an examination of existing procedures with the odds of stressing the need for an intelligent multi-document resumer.

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2020-12-30

Issue

Volume 7, Issue 6, November-December-2020

Section

Research Articles

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Copyright (c) IJSRSET

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Rajat Bodankar, Mayuri Waghmare "Identification and Effective Summary Extraction with Deduplication of Data in News Articles" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 7, Issue 6, pp.96-102, November-December-2020. Available at doi : https://doi.org/10.32628/IJSRSET207620