Knowledge Graphs as Context Models: Improving the Detection of Cross-Language Plagiarism with Paraphrasing

Handle

https://riunet.upv.es/handle/10251/49758

Citation

Franco-Salvador, M.; Gupta, P.; Rosso, P. (2013). Knowledge Graphs as Context Models: Improving the Detection of Cross-Language Plagiarism with Paraphrasing. En Bridging Between Information Retrieval and Databases: PROMISE Winter School 2013, Bressanone, Italy, February 4-8, 2013. Revised Tutorial Lectures. Springer Verlag (Germany). 227-236. https://doi.org/10.1007/978-3-642-54798-0_12

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Abstract

Cross-language plagiarism detection attempts to identify and extract automatically plagiarism among documents in different languages. Plagiarized fragments can be translated verbatim copies or may alter their structure to hide the copying, which is known as paraphrasing and is more difficult to detect. In order to improve the paraphrasing detection, we use a knowledge graph-based approach to obtain and compare context models of document fragments in different languages. Experimental results in German-English and Spanish-English cross-language plagiarism detection indicate that our knowledge graph-based approach offers a better performance compared to other state-of-the-art models.

Source

Bridging Between Information Retrieval and Databases: PROMISE Winter School 2013, Bressanone, Italy, February 4-8, 2013. Revised Tutorial Lectures isbn: 978-3-642-54797-3 issn: 0302-9743

Publisher

Springer Verlag (Germany)

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