Semantically-informed distance and similarity measures for paraphrase plagiarism identification-Reference-Cited by-同舟云学术

Semantically-informed distance and similarity measures for paraphrase plagiarism identification

Published:2018-05-24 Issue:5 Volume:34 Page:2983-2990
ISSN:1064-1246
Container-title:Journal of Intelligent & Fuzzy Systems
language:
Short-container-title:IFS

Author:

Álvarez-Carmona Miguel A.¹,Franco-Salvador Marc²,Villatoro-Tello Esaú³,Montes-y-Gómez Manuel¹,Rosso Paolo⁴,Villaseñor-Pineda Luis¹

Affiliation:

1. Department of Computer Science, Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE), Mexico

2. Symanto Research, Nuremberg, Germany

3. Department of Information Technologies, Language and Reasoning Research Group, Universidad Autónoma Metropolitana, Unidad Cuajimalpa (UAM-C), Mexico

4. PRHLT Research Center, Universitat Politècnica de València, Spain

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference20 articles.

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3. Biggins S. , Mohammed S. and Oakley S. , University of shefield: Two approaches to semantic text similarity, In First Joint Conference on Lexical and Computational Semantics (SEM at NAACL 2012), Montreal, Canada, 2012, pp. 655–661.

4. Plagiarism detection using word2vec model. p;Brlek;Text Analysis and Retrieval 2016 Course Project Reports,2016

5. Chatterjee K. , Henzinger T.A. , Ibsen-Jensen R. and Otop J. , Edit distance for pushdown automata. arXiv preprint arXiv:1504.08259, 2015.

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