Онтолошко препознавање реторичких фигура
Abstract
Аутоматско препознавање реторичких фигура (компарације, ироније, сарказма, хумора, метафоре и сл.) све чешће се користи у задацима обраде природног језика, пре свега за унапређење система класификације текста према осећањима, машинског превођења, али и система који анализирају језичке структуре на различитим нивоима. У овом раду предложена је метода аутоматског препознавања и класификације реторичких фигура из групе тропи која користи правила онтолошког закључивања у онтологији Српски ворднет (SWN). Евалуација методе изведена је над реторичком фигуром компарација, а статистичка оцена бинарног класификатора ROC кривом (AUC=0.696) указује да се он може успешно користити у решавању ове врсте задатака. За даље обучавање онтологије SWN, предложена је полу-аутоматска метода учења онтологије повећањем броја и врста релација које могу помоћи у откривању фигуративног говора у текстовима на српском језику.References
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Mladenović, M., & Mitrović, J. (2014). Semantic Networks for Serbian: New Functionalities of Developing and Maintaining a WordNet Tool. In G. Pavlović Lažetić, C. Krstev, I. Obradović & D. Vitas Natural Language Processing for Serbian – Resources and Application, 1-11. Matematički fakultet, Beograd.
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Mladenović, M., Mitrović, J., Krstev, C., & Vitas, D. (2015). Hybrid Sentiment Analysis Framework For A Morphologically Rich Language. Journal of Intelligent Information Systems (In Press, Available online 15 August 2015).
Nicolae, C., Nicolae, G., & Harabagiu, S. (2007). In Proceedings of the Fourth International Workshop on Semantic Evaluations (SemEval-2007), 454–459. Association for Computational Linguistics.
Pang, B., Lee, L., & Vaithyanathan, S. (2002). Thumbs up? Sentiment Classification using Machine Learning Techniques. In Proceedings of the ACL-02 conference on Empirical Methods in Natural Language Processing (EMNLP), 10, 79–86.
Poesio, M., & Artstein, R. (2008). Anaphoric Annotation in the ARRAU Corpus. In Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08).
Rentoumi, V., Petrakis, S., Klenner, M., Vouros, A. G., & Karkaletsis, V. (2010). United we stand - improving sentiment analysis by joining machine learning and rule based methods. In Proceedings of the 7th Language Resources and Evaluation Conference (LREC 2010).
Reyes, A., & Rosso, P. (2012a). Building Corpora for Figurative Language Processing: The Case of Irony Detection. In Proceedings of the 4th International Workshop on Corpora for Research on Emotion Sentiment & Social Signals, 94–98.
Reyes, A., & Rosso, P. (2012b). Making objective decisions from subjective data: Detecting irony in customer reviews. Decision Support Systems, 53(4), 754–760.
Shutova, E., Teufel, S., & Korhonen, A. (2013). Statistical Metaphor Processing. Computional Linguistics, 39(2), 301–353.
Utvić, M. (2014). Construction of a reference corpus of contemporary Serbian language (doctoral dissertation). Faculty of Philology, Belgrade, Serbia.
Veale, T., & Hao, Y. (2009). Support structures for linguistic creativity: a computational analysis of creative irony in similes. In Proceedings of CogSci 2009, the 31st annual meeting of the cognitive science society (pp. 1376–1381).
Veale, T. (2012). Detecting and Generating Ironic Comparisons: An Application of Creative Information Retrieval. Artificial Intelligence of Humor, Papers from the 2012 {AAAI} Fall Symposium, Arlington, Virginia, USA, November 2-4, 2012, FS-12-02.
Williams, L., Bannister, C., Arribas-Ayllon, M., Preece, A., & Spasić., A. (2015). The role of idioms in sentiment analysis. Expert Systems with Applications, 42(21), 7375 – 7385.
Bagić, K. (2012). Rječnik stilskih figura. Školska knjiga, Zagreb.
Barbieri, F., Ronzano, F., & Saggion, H. (2015). UPF-taln: SemEval 2015 Tasks 10 and 11. Sentiment Analysis of Literal and Figurative Language in Twitter. In Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015), 704–708.
Bobrow, D.G. (1964). A question-answering system for high school algebra word problems. In Proceedings of AFIPS conference, 26. FJCC.
Carvalho, P., Sarmento, L., Silva, M. J., & de Oliveira, E. (2009). Clues for Detecting Irony in User-generated Contents: Oh...!! It's "So Easy" ;-). In Proceedings of the 1st International CIKM Workshop on Topic-sentiment Analysis for Mass Opinion, 53–56.
Carvalho, P., Sarmento, L., Teixeira, J., & Silva, M. J. (2011). Liars and Saviors in a Sentiment Annotated Corpus of Comments to Political Debates. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: Short Papers, 2, 564–568.
Davidov, D., Tsur, O., & Rappoport, A. (2010). A Great Catchy Name: Semi-Supervised Recognition of Sarcastic Sentences in Online Product Reviews. In Proceedings of the Fourth International AAAI Conference on Weblogs and Social Media (ICWSM-2010).
Devedžić, V. (2006). Semantic Web and Education, Monograph. Springer, Berlin Heidelberg New York.
Farkas, R., Simon, E., Szarvas, Gy., & Varga, D. (2007). Gyder: Maxent metonymy resolution. In Proceedings of the Fourth International Workshop on Semantic Evaluations (SemEval-2007), 161–164. Association for Computational Linguistics.
Fass, D. (1991). met*:A method for discriminating metonymy and metaphor by computer. Computational Linguistics, 17(1), 49–90.
Fellbaum, C. (Ed). (1998). WordNet: An Electronic Lexical Database. Cambridge, MA: MIT Press.
Filatova, Е. (2012). Irony and sarcasm: Corpus generation and analysis using crowdsourcing. In Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC’12), 392–398.
Gawryjolek, J., Di Marco, C., & Harris, R. A. (2009). An Annotation Tool for Automatically Detecting Rhetorical Figures – System Demonstration. In Proceedings of the IJCAI-09 workshop on Computational Models of Natural Argument. Pasadena, CA.
González-Ibáñez, R., Muresan, S., & Wacholder, N. (2011). Identifying sarcasm in Twitter: a closer look. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics:shortpapers (ACL-2011).
Gruber, T. R. (1993). A translation approach to portable ontologies. Knowledge Acquisition, 5(2), 199–220. Retrieved September 20, 2015, from website: http://tomgruber.org/writing/ontolingua-kaj-1993.htm
Hao, Y., & Veale, T. (2010). An Ironic Fist in a Velvet Glove: Creative Mis-Representation in the Construction of Ironic Similes. Journal Minds and Machines, 20(4), 635–650.
Hardie, A., Koller, V., Rayson, P., & Semino, E. (2007). Exploiting a semantic annotation tool for metaphor analysis. In M. Davies, P. Rayson, S. Hunston & P. Danielsson (Eds.), Proceedings of the Corpus Linguistics 2007 Conference.
Harris, R. A., & Di Marco, C. (2009). Constructing a rhetorical figuration ontology. Symposium on Persuasive Technology and Digital Behavior Intervention, Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour (AISB), 47–52. Edinburgh.
Hromada, D. D. (2011). Initial Experiments with Multilingual Extraction of Rhetoric Figures by means of PERL-compatible Regular Expressions. In Proceedings of the Student Research Workshop associated with The 8th International Conference on Recent Advances in Natural Language Processing (RANLP), 85–90.
Kelly, A. R., Abbott, N. A., Harris, R. A., Di Marco, C., & Cheriton, D. R. (2010). Toward an ontology of rhetorical figures. In Proceedings of the 28th ACM International Conference on Design of Communication SIGDOC '10, 123–130.
Kennedy, A., & Inkpen, D. (2006). Sentiment Classification of Movie Reviews Using Contextual Valence Shifters. Computational Intelligence (special issue), 22(2), 110–125.
Koeva, S., Krstev, C., & Vitas, D. (2008). Morpho-semantic Relations in WordNet - a Case Study for two Slavic Languages. In Proceedings of Global WordNet Conference, 239–253. University of Szeged.
Koller, V., Hardie, A., Rayson, P., & Semino, E. (2008). Using a semantic annotation tool for the analysis of metaphor in discourse. metaphorik.de, 15, 141–160.
Leveling, Ј. FUH (FernUniversität in Hagen): Metonymy Recognition Using Different Kinds of Context for a Memory-Based Learner. In Proceedings of the Fourth International Workshop on Semantic Evaluations (SemEval-2007), 153–156. Association for Computational Linguistics
Markert, K., & Nissim, M. (2002). Metonymy resolution as a classification task. In Proceedings of EMNLP, 204–213.
Mason, Z. (2004) CorMet: a computationa l, corpus-based conventional metaphor extraction system. Computational Linguistics, 30(1), 23–44.
Mitkov, R. (2002). Anaphora Resolution. Longman. Cambridge, UK.
Mitrović, J. (2014). Electronic Tools and Resources for Multi-Word Unit Detection and Research in Serbian. Poster at Тhe 2th General Meeting of The IC1207 COST Action, PARSEME. Athens, Greece, 10-11 March, 2014.
Mitrović, J., Mladenović, M., & Krstev, C. (2015). Adding MWEs to Serbian Lexical Resources Using Crowdsourcing. Poster at Тhe 5th PARSEME general meeting. Iași, Romania, 23–24 September 2015.
Mladenović, M., & Mitrović, J. (2013). Ontology of Rhetorical Figures for Serbian. Text, Speech and Dialogue, 386–393. Lecture Notes in Computer Science 8082. Springer.
Mladenović, M., & Mitrović, J. (2014). Semantic Networks for Serbian: New Functionalities of Developing and Maintaining a WordNet Tool. In G. Pavlović Lažetić, C. Krstev, I. Obradović & D. Vitas Natural Language Processing for Serbian – Resources and Application, 1-11. Matematički fakultet, Beograd.
Mladenović, M., Mitrović, J., & Krstev, C. (2016). Introducing a Language-independent Model for Adding a New Semantic Relation Between Adjectives and Nouns in a WordNet. Paper accepted to be presented at Eight Global WordNet Conference 2016.
Mladenović, M., Mitrović, J., Krstev, C., & Vitas, D. (2015). Hybrid Sentiment Analysis Framework For A Morphologically Rich Language. Journal of Intelligent Information Systems (In Press, Available online 15 August 2015).
Nicolae, C., Nicolae, G., & Harabagiu, S. (2007). In Proceedings of the Fourth International Workshop on Semantic Evaluations (SemEval-2007), 454–459. Association for Computational Linguistics.
Pang, B., Lee, L., & Vaithyanathan, S. (2002). Thumbs up? Sentiment Classification using Machine Learning Techniques. In Proceedings of the ACL-02 conference on Empirical Methods in Natural Language Processing (EMNLP), 10, 79–86.
Poesio, M., & Artstein, R. (2008). Anaphoric Annotation in the ARRAU Corpus. In Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08).
Rentoumi, V., Petrakis, S., Klenner, M., Vouros, A. G., & Karkaletsis, V. (2010). United we stand - improving sentiment analysis by joining machine learning and rule based methods. In Proceedings of the 7th Language Resources and Evaluation Conference (LREC 2010).
Reyes, A., & Rosso, P. (2012a). Building Corpora for Figurative Language Processing: The Case of Irony Detection. In Proceedings of the 4th International Workshop on Corpora for Research on Emotion Sentiment & Social Signals, 94–98.
Reyes, A., & Rosso, P. (2012b). Making objective decisions from subjective data: Detecting irony in customer reviews. Decision Support Systems, 53(4), 754–760.
Shutova, E., Teufel, S., & Korhonen, A. (2013). Statistical Metaphor Processing. Computional Linguistics, 39(2), 301–353.
Utvić, M. (2014). Construction of a reference corpus of contemporary Serbian language (doctoral dissertation). Faculty of Philology, Belgrade, Serbia.
Veale, T., & Hao, Y. (2009). Support structures for linguistic creativity: a computational analysis of creative irony in similes. In Proceedings of CogSci 2009, the 31st annual meeting of the cognitive science society (pp. 1376–1381).
Veale, T. (2012). Detecting and Generating Ironic Comparisons: An Application of Creative Information Retrieval. Artificial Intelligence of Humor, Papers from the 2012 {AAAI} Fall Symposium, Arlington, Virginia, USA, November 2-4, 2012, FS-12-02.
Williams, L., Bannister, C., Arribas-Ayllon, M., Preece, A., & Spasić., A. (2015). The role of idioms in sentiment analysis. Expert Systems with Applications, 42(21), 7375 – 7385.
Published
2016-05-14
How to Cite
МЛАДЕНОВИЋ, Миљана.
Онтолошко препознавање реторичких фигура.
Infotheca - Journal for Digital Humanities, [S.l.], v. 16, n. 1-2a, may 2016.
ISSN 2217-9461.
Available at: <https://infoteka.bg.ac.rs/ojs/index.php/Infoteka/article/view/2016.16.1_2.2_sr>. Date accessed: 19 nov. 2024.
Section
Articles
Keywords
figurative speech, similes classification, ontology based classification, WordNet
