SLIIT >
NCTM - SLIIT >
NCTM - SLIIT 2009 >

Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/219

Title: Document Fingerprint Detection System
Authors: Rathnayake, R.M.A.S.B
Emitiyagoda, G.A.M.U.W
Mudannayake, M.A.L.G
Jayathilake, K.H.B.H.C
Rajapaksha, U.U.S.K
Keywords: Document Finger Print Detection System
Winnowing Algorithm
Token step
k-gram
Tokens
Issue Date: Dec-2009
Publisher: SLIIT
Citation: PSRS2009
Series/Report no.: SLIIT/LIB/;
Abstract: DFDS is developed to prevent copying someone else’s work as your own work which is known as “Plagiarism”. Plagiarism is a growing problem in all universities, colleges and schools today. Detection can be done either manually or in a computer-assisted manner. Manual detection requires substantial effort and excellent memory to identify, and it is impractical in cases where too many documents must be compared, or original documents are not available for comparison. Computer-assisted detection allows vast collections of documents to be compared to each other, attempts to obtain, make successful detection. By using DFDS one is able to find copying that the student has done in assignments from others and online web documents. To improve producing of most accurate results than existing systems, Document Fingerprint Detection system has used most suitable hash function, algorithm, searching method and comparison methods. System takes student assignments as inputs. Sends the document to the parsing module. It clears unnecessary punctuation marks, white spaces, letter cases and refines the document. Token manager takes input as a refined document and then the document is divided into Tokens. Creates hash values for each token and generates fingerprint which select some tokens out of all tokens. Those tokens are sent to web search engine. The system searches suspect documents that is similar to assignment. System downloads some suspect documents from web and compares local student documents with those downloaded documents. Finally generates percentage of own work, web copied work, suspect work, referred text, percentage of friend’s work and student identity numbers to detect copied from original document.
URI: http://hdl.handle.net/123456789/219
ISSN: 1800-3591
Appears in Collections:NCTM - SLIIT 2009

Files in This Item:

File Description SizeFormat
Page 86-89.pdf208.88 kBAdobe PDFView/Open
View Statistics

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback