A systematic study of knowledge graph analysis for cross-language plagiarism detection

被引：64
|
作者：
Franco-Salvador, Marc [1 ]
Rosso, Paolo [1 ]
Montes-y-Gomez, Manuel [2 ]
机构：
[1] Univ Politecn Valencia, Pattern Recognit & Human Language Technol PRHLT R, Camino Vera S-N, E-46022 Valencia, Spain
[2] Inst Nacl Astrofis Opt & Electr, Dept Comp Sci, Luis Enrique Erro 1, Puebla 72840, Mexico
来源：
INFORMATION PROCESSING & MANAGEMENT | 2016年 / 52卷 / 04期
关键词：
Cross-language; Plagiarism detection; Knowledge graphs; Multilingual semantic network; Distributed representations; Evaluation;
D O I：
10.1016/j.ipm.2015.12.004
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码：550 / 570
页数：21
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