Title | ||
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A systematic study of knowledge graph analysis for cross-language plagiarism detection. |
Abstract | ||
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Study of the impact of the implicit aspects of knowledge graphs for cross-language plagiarism detection.We present a new weighting scheme for relations between concepts based on distributed representations of concepts.We obtain state-of-the-art performance compared to several state-of-the-art models. 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 cross-language 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. |
Year | DOI | Venue |
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2016 | 10.1016/j.ipm.2015.12.004 | Inf. Process. Manage. |
Keywords | Field | DocType |
Cross-language,Plagiarism detection,Knowledge graphs,Multilingual semantic network,Distributed representations,Evaluation | Data mining,Weighting,Knowledge graph,Plagiarism detection,Computer science,Natural language processing,Artificial intelligence,Graph,Information retrieval,Knowledge economy,Content Model,Vocabulary,Word-sense disambiguation | Journal |
Volume | Issue | ISSN |
52 | 4 | 0306-4573 |
Citations | PageRank | References |
28 | 0.91 | 36 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
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Marc Franco-Salvador | 1 | 111 | 10.06 |
Paolo Rosso | 2 | 66 | 4.71 |
Manuel Montes-Y-Gómez | 3 | 638 | 83.97 |