Franco-Salvador, M.; Rosso, P.; Montes Gomez, M. (2016)  Cross-language plagiarism detection aims to detect plagiarised fragments of text among documents in different languages. In this paper, we perform a systematic examination of Cross-language Knowledge Graph Analysis; an approach that represents text fragments using knowledge graphs as a language independent content model. We analyse the contributions to crosslanguage plagiarism detection of the different aspects covered by knowledge graphs: word sense disambiguation, vocabulary expansion, and representation by similarities with a collection of concepts. In addition, we study both the relevance of concepts and their relations when detecting plagiarism. Finally, as a key component of the knowledge graph construction, we present a new weighting scheme of relations between concepts based on distributed representations of concepts. Experimental results in Spanish-English and German-English plagiarism detection show state-of-the-art performance and provide interesting insights on the use of knowledge graphs.
They further showed that weighing both the concepts and the relations between the concepts in their knowledge graph, using distributed representation of concepts outperforms the CL-ESA method REF .
A systematic study of knowledge graph analysis for cross-language plagiarism detection
Inf. Process. Manag.
Inf. Process. Manag.
Computer Science