Keywords

plagiarism, sentence similarity, copyright, SimPaD

Abstract

Plagiarism is a serious problem that infringes copyrighted documents/materials, which is an unethical practice and decreases the economic incentive received by authors (owners) of the original copies. Unfortunately, plagiarism is getting worse due to the increasing number of online publications on the Web, which facilitates locating and paraphrasing information. In solving this problem, we propose a novel plagiarism-detection method, called SimPaD, which (i) establishes the degree of resemblance between any two documents D1 and D2 based on their sentence-to-sentence similarity computed by using pre-defined word-correlation factors, and (ii) generates a graphical view of sentences that are similar (or the same) in D1 and D2. Experimental results verify that SimPaD is highly accurate in detecting (non-)plagiarized documents and outperforms existing plagiarism-detection approaches.

Original Publication Citation

Nathaniel Gustafson, Maria Soledad Pera, and Yiu-Kai Ng. "Nowhere to Hide: Finding Plagiarized Documents Based on Sentence Similarity." In Proceedings of the 28 IEEE/WIC/ACM International Conference on Web Intelligence (WI'8), pp. 69-696, December 9-12, 28, Sydney, Australia.

Document Type

Peer-Reviewed Article

Publication Date

2008-12-09

Permanent URL

http://hdl.lib.byu.edu/1877/2632

Publisher

IEEE

Language

English

College

Physical and Mathematical Sciences

Department

Computer Science

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