Title :
Automatic external Persian plagiarism detection using vector space model
Author :
Mahdavi, Peyman ; Siadati, Zahra ; Yaghmaee, Farzin
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Semnan, Semnan, Iran
Abstract :
Nowadays, extremely wide and facilitated access to the Internet has made the plagiarism and text reuse more common. Many studies have been conducted on automatic plagiarism detection. But there are few studies on automatic Persian plagiarism detection methods due to lack of a suitable Persian corpus. In this paper, an external Persian plagiarism detection method based on the vector space model (VSM) has been proposed. To implement and examine this method, a Persian corpus has been developed. Several optimizations have been done during the study. These optimizations make the algorithm very fast and accurate. The test results of the proposed method shows an accuracy of 0.87 and a processing time cost of less than 10 minutes.
Keywords :
natural language processing; text analysis; Internet access; Persian corpus; VSM; automatic external Persian plagiarism detection method; processing time; text reuse; vector space model; Accuracy; Encoding; Measurement; Optimization; Plagiarism; Training; Vectors; Persian corpus; Persian plagiarism detection; automatic plagiarism detection; external detection; vector space model;
Conference_Titel :
Computer and Knowledge Engineering (ICCKE), 2014 4th International eConference on
Conference_Location :
Mashhad
Print_ISBN :
978-1-4799-5486-5
DOI :
10.1109/ICCKE.2014.6993398