CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

SCISSOR- Auto-Extraction Tool to Boost Document Scanning

by Jaini Vora, Chetashri Deshmukh
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 114 - Number 4
Year of Publication: 2015
Authors: Jaini Vora, Chetashri Deshmukh
10.5120/19965-1809

Jaini Vora, Chetashri Deshmukh . SCISSOR- Auto-Extraction Tool to Boost Document Scanning. International Journal of Computer Applications. 114, 4 ( March 2015), 12-15. DOI=10.5120/19965-1809

@article{ 10.5120/19965-1809,
author = { Jaini Vora, Chetashri Deshmukh },
title = { SCISSOR- Auto-Extraction Tool to Boost Document Scanning },
journal = { International Journal of Computer Applications },
issue_date = { March 2015 },
volume = { 114 },
number = { 4 },
month = { March },
year = { 2015 },
issn = { 0975-8887 },
pages = { 12-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume114/number4/19965-1809/ },
doi = { 10.5120/19965-1809 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:51:47.591202+05:30
%A Jaini Vora
%A Chetashri Deshmukh
%T SCISSOR- Auto-Extraction Tool to Boost Document Scanning
%J International Journal of Computer Applications
%@ 0975-8887
%V 114
%N 4
%P 12-15
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Text summarization has become an important tool for assisting and interpreting text information in today's fast-growing information age. It is very difficult and time consuming for human beings to manually summarize large documents of text. This paper discusses 'Scissor', the simple yet reliable tool, which allows the creation of a shortened version of a text by a computer program. The output of this tool contains only the most important points of the original text.

References
  1. Gunes Erkan and Dragomir R. Radev. 2011. LexRank: Graph-based Lexical Centrality as Salience in Text Summarization.
  2. Dipanjay Das. 2007. A Survey on Automatic Text Summarization
  3. Elena Lloret. Text Summarization:An Overview.
  4. Rafeeq Al-Hashemi. 2010. Text Summarization Extraction System (TSES) Using Extracted Keywords.
  5. Dalianis. 2010. SweSum - A Text Summarizer for Swedish Technical report
  6. Martin Hassel. 2004. Evaluation of Automatic Text Summarization Licentiate Thesis Stockholm
  7. Ani Nenkova, Lucy Vanderwende and Kathleen McKeown. 2006. A Compositional Context Sensitive Multi-document Summarizer: Exploring the Factors That Influence Summarization.
Index Terms

Computer Science
Information Sciences

Keywords

Scissor Extraction Summary Sentences Cardinality

Powered by PhDFocusTM