A Survey on Multi-Document Summarizer

Authors

  • Meeta B. Fadnavis  Lecturer, Department of Computer Management, Dharampeth Polytechnic, Nagpur, Maharashtra, India

Keywords:

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

Abstract

Natural language processing provides Text Summarization which is the most popular application for information compression. Text summarization is a process of producing a summary by reducing the size of original document and pertaining important information of original document. There is arising a need to provide high quality summary in less time because in present time, the growth of data increases tremendously on World Wide Web or on user’s desktops so Multi-Document summarization is the best tool for making summary in less time. This paper presents a survey of existing techniques with the novelties highlighting the need of intelligent Multi-Document summarizer.

References

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Published

2018-07-30

Issue

Section

Research Articles

How to Cite

[1]
Meeta B. Fadnavis, " A Survey on Multi-Document Summarizer, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 9, pp.59-68, July-August-2018.