A Survey on Multi-Document Summarizer

Authors(1) :-Meeta B. Fadnavis

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 userís 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.

Authors and Affiliations

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

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

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Publication Details

Published in : Volume 4 | Issue 9 | July-August 2018
Date of Publication : 2018-07-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 59-68
Manuscript Number : IJSRSET18486
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

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.
Journal URL : http://ijsrset.com/IJSRSET18486

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