Intelligent Bar Chart Plagiarism Detection in Documents-Reference-Cited by-同舟云学术

Intelligent Bar Chart Plagiarism Detection in Documents

Published:2014 Issue: Volume:2014 Page:1-11
ISSN:2356-6140
Container-title:The Scientific World Journal
language:en
Short-container-title:The Scientific World Journal

Author:

Al-Dabbagh Mohammed Mumtaz¹²,Salim Naomie¹,Rehman Amjad³^ORCID,Alkawaz Mohammed Hazim¹²,Saba Tanzila⁴,Al-Rodhaan Mznah⁵,Al-Dhelaan Abdullah⁵

Affiliation:

1. Faculty of Computing, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia

2. Faculty of Computer Sciences and Mathematics, University of Mosul, Mosul, Iraq

3. MIS Department, CBA, Salman Bin Abdulaziz University, Alkharj, Saudi Arabia

4. College of Computer and Information Sciences (CCIS), Prince Sultan University, Riyadh, Saudi Arabia

5. Computer Science Department, College of Computer & Information Sciences, King Saud University, Riyadh, Saudi Arabia

Abstract

This paper presents a novel features mining approach from documents that could not be mined via optical character recognition (OCR). By identifying the intimate relationship between the text and graphical components, the proposed technique pulls out the Start, End, and Exact values for each bar. Furthermore, the word 2-gram and Euclidean distance methods are used to accurately detect and determine plagiarism in bar charts.

Publisher

Hindawi Limited

Subject

General Environmental Science,General Biochemistry, Genetics and Molecular Biology,General Medicine

Link

http://downloads.hindawi.com/journals/tswj/2014/612787.pdf

Reference20 articles.

1. Features extraction for soccer video semantic analysis: current achievements and remaining issues

2. Evaluation of artificial intelligent techniques to secure information in enterprises

3. Understanding Plagiarism Linguistic Patterns, Textual Features, and Detection Methods

4. ANALYSIS OF VISION BASED SYSTEMS TO DETECT REAL TIME GOAL EVENTS IN SOCCER VIDEOS

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