Intelligent Bar Chart Plagiarism Detection in Documents - Mohammed Mumtaz Al-Dabbagh; Naomie Salim; Amjad Rehman; Mohammed Hazim Alkawaz; Tanzila Saba; Mznah Al-Rodhaan; Abdullah Al-Dhelaan (The Scientific World Journal)
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.