|
Twitter
|
Facebook
|
Google+
|
VKontakte
|
LinkedIn
|
Viadeo
|
English
|
Français
|
Español
|
العربية
|
 
International Journal of Innovation and Applied Studies
ISSN: 2028-9324     CODEN: IJIABO     OCLC Number: 828807274     ZDB-ID: 2703985-7
 
 
Thursday 28 March 2024

About IJIAS

News

Submission

Downloads

Archives

Custom Search

Contact

  • Contact us
  • Newsletter:

Connect with IJIAS

  Now IJIAS is indexed in EBSCO, ResearchGate, ProQuest, Chemical Abstracts Service, Index Copernicus, IET Inspec Direct, Ulrichs Web, Google Scholar, CAS Abstracts, J-Gate, UDL Library, CiteSeerX, WorldCat, Scirus, Research Bible and getCited, etc.  
 
 
 

Literature Review of Automatic Multiple Documents Text Summarization


Volume 3, Issue 1, May 2013, Pages 121–129

 Literature Review of Automatic Multiple Documents Text Summarization

Md. Majharul Haque1, Suraiya Pervin2, and Zerina Begum3

1 Department of Computer Science & Engineering, University of Dhaka, Dhaka, Bangladesh
2 Department of Computer Science & Engineering, University of Dhaka, Dhaka, Bangladesh
3 Institute of Information Technology, University of Dhaka, Dhaka, Bangladesh

Original language: English

Copyright © 2013 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract


For the blessing of World Wide Web, the corpus of online information is gigantic in its volume. Search engines have been developed such as Google, AltaVista, Yahoo, etc., to retrieve specific information from this huge amount of data. But the outcome of search engine is unable to provide expected result as the quantity of information is increasing enormously day by day and the findings are abundant. So, the automatic text summarization is demanded for salient information retrieval. Automatic text summarization is a system of summarizing text by computer where a text is given to the computer as input and the output is a shorter and less redundant form of the original text. An informative pr

Author Keywords: World Wide Web, Search engine, Information retrieval, Document abridgement, Human expert.


How to Cite this Article


Md. Majharul Haque, Suraiya Pervin, and Zerina Begum, “Literature Review of Automatic Multiple Documents Text Summarization,” International Journal of Innovation and Applied Studies, vol. 3, no. 1, pp. 121–129, May 2013.