Title
A systematic study of knowledge graph analysis for cross-language plagiarism detection.
Abstract
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
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
Marc Franco-Salvador111110.06
Paolo Rosso2664.71
Manuel Montes-Y-Gómez363883.97