Plagiarism Detection Based on Singular Value Decomposition

Authors:
Zdenek Ceska
Affiliations:
Department of Computer Science and Engineering, Faculty of Applied Sciences, University of West Bohemia, Pilsen, Czech Republic 306 14
Venue:
GoTAL '08 Proceedings of the 6th international conference on Advances in Natural Language Processing
Year:
2008

Citing 7
Cited 6

Term-weighting approaches in automatic text retrieval

Information Processing and Management: an International Journal
Using linear algebra for intelligent information retrieval

SIAM Review
Copy detection mechanisms for digital documents

SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Building a scalable and accurate copy detection mechanism

Proceedings of the first ACM international conference on Digital libraries
Foundations of statistical natural language processing

Foundations of statistical natural language processing
Detection of Duplicate Defect Reports Using Natural Language Processing

ICSE '07 Proceedings of the 29th international conference on Software Engineering
PPChecker: plagiarism pattern checker in document copy detection

TSD'06 Proceedings of the 9th international conference on Text, Speech and Dialogue

Finding inner copy communities using social network analysis

KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part II
SimPaD: A word-similarity sentence-based plagiarism detection tool on Web documents

Web Intelligence and Agent Systems
An automatic text comprehension classifier based on mental models and latent semantic features

i-KNOW '11 Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies
Retrieving candidate plagiarised documents using query expansion

ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
Using structural information and citation evidence to detect significant plagiarism cases in scientific publications

Journal of the American Society for Information Science and Technology
Text mining applied to plagiarism detection: The use of words for detecting deviations in the writing style

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

Plagiarism is a widely spread problem that is the main focus of interest these days. In this paper, we propose a new method solving associations of phrases contained in text documents. This method, called SVDPlag, employs Singular Value Decomposition (SVD) for this purpose. Further, we discuss other approaches to plagiarism detection and compare them with our method. To examine the efficiency of plagiarism detection methods, we used an experimental corpus of 950 text documents about politics, which were created from the standard CTK corpus. The experiments indicate that our approach significantly improves the accuracy of plagiarism detection and overcomes other methods.