A Survey on Various Techniques for Multi-Document Summarization

Authors

  • Apurva Sawwalakhe  BE, Department of Computer Science and Engineering, Shrimati Rajshree Mulak College of Engineering, Nagpur, Maharashtra, India
  • Nikita Wanjari  BE, Department of Computer Science and Engineering, Shrimati Rajshree Mulak College of Engineering, Nagpur, Maharashtra, India
  • Shreya Paliwal  BE, Department of Computer Science and Engineering, Shrimati Rajshree Mulak College of Engineering, Nagpur, Maharashtra, India
  • Shubhangi Katare  BE, Department of Computer Science and Engineering, Shrimati Rajshree Mulak College of Engineering, Nagpur, Maharashtra, India
  • Vidhya Malve  BE, Department of Computer Science and Engineering, Shrimati Rajshree Mulak College of Engineering, Nagpur, Maharashtra, India

Keywords:

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

Abstract

Natural language processing gives Text Summarization which is the most well-known application for data pressure. Content rundown is a procedure of creating a synopsis by decreasing the span of unique report and relating critical data of unique record. There is emerging a need to give top notch synopsis in less time on the grounds that in present time, the development of information increments massively on World Wide Web or on client's desktops so Multi-Document outline is the best apparatus for making rundown in less time. This paper introduces a study of existing techniques with the curiosities highlighting the need of astute Multi-Document summarizer.

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International Journal of Scientific Research in Science and Technology

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Published

2019-02-28

Issue

Volume 6, Issue 1, January-February-2019

Section

Research Articles

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How to Cite

[1]
Apurva Sawwalakhe, Nikita Wanjari, Shreya Paliwal, Shubhangi Katare, Vidhya Malve, " A Survey on Various Techniques for Multi-Document Summarization, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 6, Issue 1, pp.513-520, January-February-2019.