Name
Abstract | ||
|---|---|---|
Cross language plagiarism is the unacknowledged reuse of text across language pairs. It occurs if a passage of text is translated from source language to target language and no proper citation is provided. Although various methods have been developed for detection of cross language plagiarism, less attention has been paid to measure and compare their performance, especially when tackling with different types of paraphrasing through translation. In this paper, we investigate various approaches to cross language plagiarism detection. Moreover, we present a novel approach to cross language plagiarism detection using word embedding methods and explore its performance against other state-of-the-art plagiarism detection algorithms. In order to evaluate the methods, we have constructed an English-Persian bilingual plagiarism detection corpus (referred to as HAMTA-CL) comprised of seven types of obfuscation. The results show that the word embedding approach outperforms the other approaches with respect to recall when encountering heavily paraphrased passages. On the other hand, translation based approach performs well when the precision is the main consideration of the cross language plagiarism detection system. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3233/IDA-183985 | INTELLIGENT DATA ANALYSIS |
Keywords | Field | DocType |
Cross-language plagiarism detection, low resource languages, distant language pairs, text re-use | Plagiarism detection,Computer science,Artificial intelligence,Natural language processing,Word embedding,Machine learning | Journal |
Volume | Issue | ISSN |
23 | 3 | 1088-467X |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Habibollah Asghari | 1 | 10 | 4.92 |
| Omid Fatemi | 2 | 78 | 15.71 |
| Salar Mohtaj | 3 | 0 | 0.34 |
| Heshaam Faili | 4 | 104 | 28.10 |
| paolo rosso | 5 | 1831 | 188.74 |