Paraphrase plagiarism identification with character-level features

Author:

Sánchez-Vega Fernando,Villatoro-Tello EsaúORCID,Montes-y-Gómez Manuel,Rosso Paolo,Stamatatos Efstathios,Villaseñor-Pineda Luis

Funder

CONACYT Mexico

SomEMBED

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition

Reference37 articles.

1. Barrón-Cedeño A, Rosso P (2009) On automatic plagiarism detection based on n-grams comparison. In: Proceedings of the 31th European conference on IR research on advances in information retrieval (ECIR), LNCS vol 5478, Springer, Berlin, pp 696–700

2. Barron-Cedeño A, Vila M, Martí MA, Rosso P (2013) Plagiarism meets paraphrasing: insights for the next generation in automatic plagiarism detection. Comput Linguist 39(4):917–947

3. Basile C, Benedetto D, Caglioti E, Cristadoro G, Esposti M (2009) A plagiarism detection procedure in three steps: selection, matches and “squares”. In: Proceedings of the SEPLN 2009 workshop on uncovering plagiarism, authorship and social software misuse (PAN 2009), CEUR-WS vol 502. Donostia-San Sebastian, Spain

4. Biggins S, Mohammed S, Oakley S (2012) University of shefield: two approaches to semantic text similarity. In: First joint conference on lexical and computational semantics (SEM at NAACL 2012), Montreal, Canada, pp 655–661

5. Burrows S, Potthast M, Stein B (2013) Paraphrase acquisition via crowdsourcing and machine learning. ACM Trans Intell Syst Technol 4(3):43:1–43:21. https://doi.org/10.1145/2483669.2483676

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