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What Motivates You? Benchmarking Automatic Detection of Basic Needs from Short Posts ...
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Five Psycholinguistic Characteristics for Better Interaction with Users ...
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UH-PRHLT at SemEval-2016 Task 3: Combining Lexical and Semantic-based Features for Community Question Answering ...
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A Resource-Light Method for Cross-Lingual Semantic Textual Similarity ...
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A Low Dimensionality Representation for Language Variety Identification
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A resource-light method for cross-lingual semantic textual similarity
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Semantically-informed distance and similarity measures for paraphrase plagiarism identification
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A Cross-domain and Cross-language Knowledge-based Representation of Text and its Meaning
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A Systematic Study of Knowledge Graph Analysis for Cross-language Plagiarism Detection
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Cross-language Plagiarism Detection over Continuous-space- and Knowledge Graph-based Representations of Language
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Language variety identification using distributed representations of words and documents
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Cross-domain polarity classification using a knowledge-enhanced meta-classifier
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Detección de plagio translingüe utilizando una red semántica multilingüe
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Análisis de similitud basado en grafos: una nueva aproximación a la detección de plagio translingüe ; Graph-based similarity analysis: a new approach to cross-language plagiarism detection
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Knowledge Graphs as Context Models: Improving the Detection of Cross-Language Plagiarism with Paraphrasing
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Abstract:
Cross-language plagiarism detection attempts to identify and extract automatically plagiarism among documents in different languages. Plagiarized fragments can be translated verbatim copies or may alter their structure to hide the copying, which is known as paraphrasing and is more difficult to detect. In order to improve the paraphrasing detection, we use a knowledge graph-based approach to obtain and compare context models of document fragments in different languages. Experimental results in German-English and Spanish-English cross-language plagiarism detection indicate that our knowledge graph-based approach offers a better performance compared to other state-of-the-art models. ; The research has been carried out in the framework of the European Commission WIQ-EIIRSES (no. 269180) and DIANA-APPLICATIONS - Finding Hidden Knowledge in Texts:Applications (TIN2012-38603-C02-01) projects as well as the VLC/CAMPUS Microcluster on Multimodal Interaction in Intelligent Systems. ; Franco-Salvador, M.; Gupta, P.; Rosso, P. (2013). Knowledge Graphs as Context Models: Improving the Detection of Cross-Language Plagiarism with Paraphrasing. En Bridging Between Information Retrieval and Databases: PROMISE Winter School 2013, Bressanone, Italy, February 4-8, 2013. Revised Tutorial Lectures. Springer Verlag (Germany). 227-236. https://doi.org/10.1007/978-3-642-54798-0_12 ; S ; 227 ; 236 ; Barrón-Cedeño, A., Vila, M., Martí, M., Rosso, P.: Plagiarism meets paraphrasing: insights for the next generation in automatic plagiarism detection. Computational Linguistics 39(4) (2013) ; Barrón-Cedeño, A.: On the mono- and cross-language detection of text re-use and plagiarism. Ph.D. thesis, Universitat Politènica de València (2012) ; Barrón-Cedeño, A., Rosso, P., Pinto, D., Juan, A.: On cross-lingual plagiarism analysis using a statistical model. In: Proc. of the ECAI 2008 Workshop on Uncovering Plagiarism, Authorship and Social Software Misuse, PAN 2008 (2008) ; Franco-Salvador, M., Gupta, P., Rosso, P.: Cross-language plagiarism detection using BabelNet’s statistical dictionary. Computación y Sistemas, Revista Iberoamericana de Computación 16(4), 383–390 (2012) ; Franco-Salvador, M., Gupta, P., Rosso, P.: Cross-language plagiarism detection using a multilingual semantic network. In: Serdyukov, P., Braslavski, P., Kuznetsov, S.O., Kamps, J., Rüger, S., Agichtein, E., Segalovich, I., Yilmaz, E. (eds.) ECIR 2013. LNCS, vol. 7814, pp. 710–713. Springer, Heidelberg (2013) ; Franco-Salvador, M., Gupta, P., Rosso, P.: Graph-based similarity analysis: a new approach to cross-language plagiarism detection. Journal of the Spanish Society of Natural Language Processing (Sociedad Espaola de Procesamiento del Languaje Natural) (50) (2013) ; Montes-y-Gómez, M., Gelbukh, A., López-López, A., Baeza-Yates, R.: Flexible comparison of conceptual graphs. In: Mayr, H.C., Lazanský, J., Quirchmayr, G., Vogel, P. (eds.) DEXA 2001. LNCS, vol. 2113, pp. 102–111. Springer, Heidelberg (2001) ; Gupta, P., Barrón-Cedeño, A., Rosso, P.: Cross-language high similarity search using a conceptual thesaurus. In: Catarci, T., Forner, P., Hiemstra, D., Peñas, A., Santucci, G. (eds.) CLEF 2012. LNCS, vol. 7488, pp. 67–75. Springer, Heidelberg (2012) ; Mcnamee, P., Mayfield, J.: Character n-gram tokenization for European language text retrieval. Information Retrieval 7(1), 73–97 (2004) ; Miller, G.A., Leacock, C., Tengi, R., Bunker, R.T.: A semantic concordance. In: Proceedings of the Workshop on Human Language Technology, HLT 1993, pp. 303–308. Association for Computational Linguistics, Stroudsburg (1993) ; Navigli, R., Ponzetto, S.P.: BabelNet: The automatic construction, evaluation and application of a wide-coverage multilingual semantic network. Artificial Intelligence 193, 217–250 (2012) ; Och, F.J., Ney, H.: A systematic comparison of various statistical alignment models. Computational Linguistics 29(1), 19–51 (2003) ; Potthast, M., Barrón-Cedeño, A., Stein, B., Rosso, P.: An evaluation framework for plagiarism detection. In: Proc. of the 23rd Int. Conf. on Computational Linguistics, COLING 2010, Beijing, China, pp. 997–1005 (2010) ; Potthast, M., Barrón-Cedeño, A., Stein, B., Rosso, P.: Cross-language plagiarism detection. Language Resources and Evaluation, Special Issue on Plagiarism and Authorship Analysis 45(1), 45–62 (2011) ; Potthast, M., Eiselt, A., Barrón-Cedeño, A., Stein, B., Rosso, P.: Overview of the 3rd int. competition on plagiarism detection. In: CLEF (Notebook Papers/Labs/Workshop) (2011) ; Potthast, M., Gollub, T., Hagen, M., Kiesel, J., Michel, M., Oberländer, A., Tippmann, M., Barrón-Cedeño, A., Gupta, P., Rosso, P., et al.: Overview of the 4th international competition on plagiarism detection. In: CLEF (Online Working Notes/Labs/Workshop) (2012) ; Pouliquen, B., Steinberger, R., Ignat, C.: Automatic linking of similar texts across languages. In: Proc. Recent Advances in Natural Language Processing III, RANLP 2003, pp. 307–316 (2003) ; Schmid, H.: Probabilistic part-of-speech tagging using decision trees. In: Proc. Int. Conf. on New Methods in Language Processing (1994) ; Stein, B., zu Eissen, S.M., Potthast, M.: Strategies for retrieving plagiarized documents. In: Proc. of the 30th Annual Int. ACM SIGIR Conf. on Research and Development in Information Retrieval, pp. 825–826. ACM (2007) ; Steinberger, R., Pouliquen, B., Widiger, A., Ignat, C., Erjavec, T., Tufis, D., Varga, D.: The jrc-acquis: A multilingual aligned parallel corpus with +20 languages. In: Proc. 5th Int. Conf. on Language Resources and Evaluation, LREC 2006 (2006) ; Vossen, P.: Eurowordnet: A multilingual database of autonomous and language-specific wordnets connected via an inter-lingual index. Proc. Int. Journal of Lexicography 17 (2004)
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Keyword:
BabelNet; Cross-language plagiarism detection; Knowledge graphs; LENGUAJES Y SISTEMAS INFORMATICOS; Paraphrasing; Textual similarity
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URL: https://doi.org/10.1007/978-3-642-54798-0_12 http://hdl.handle.net/10251/49758
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Cross-language plagiarism detection using multilingual semantic network
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Análisis de similitud basado en grafos: Una nueva aproximación a la detección de plagio translingüe ; Graph-Based Similarity Analysis: A New Approach to Cross-Language Plagiarism Detection
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Detección de plagio translingüe utilizando el diccionario estadístico de BabelNet ; Cross-language Plagiarism Detection Using BabelNet’s Statistical Dictionary
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