Intelligent Bar Chart Plagiarism Detection in Documents

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. Fur...

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Bibliographic Details
Published in:TheScientificWorld 2014, Vol.2014 (2014), p.1-11
Main Authors: al-Dhelaan, Abdullah, Saba, T., Alkawaz, Mohammed Hazim, Rehman, A., Salim, Naomie, Al-Dabbagh, Mohammed Mumtaz, al-Rodhaan, Mznah
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Bar charts
Classification
Computer Graphics
Data Mining - methods
Document processing
Forgery
Grammar
Humans
Identification and classification
Image retrieval
Information science
Medical research
Methods
Natural language
Pattern Recognition, Automated - methods
Plagiarism
Safety and security measures
Semantics
Taxonomy
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Description
Summary: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.
ISSN:2356-6140
1537-744X
1537-744X
DOI:10.1155/2014/612787