Approaches to Text Simplification: Can Computer Technologies Outdo a Human Mind?
Abstract
Narrowly specialized information is addressed to a limited circle of professionals though it provokes interest among people without specialized education. This gives rise to a need for the popularization of scientific information. This process is carried out through simplified texts as a kind of secondary texts that are directly aimed at the addressee. Age, language proficiency and background knowledge are the main features which are usually taken into consideration by the author of the secondary text who makes changes in the text composition, as well as in its pragmatics, semantics and syntax. This article analyses traditional approaches to text simplification, computer simplification and summarization. The authors compare human-authored simplification of literary texts with the newest trends in computer simplification to promote further development of machine simplification tools. It has been found that the samples of simplified scientific texts seem to be more natural than the samples of simplified literary texts since technical background knowledge can be processed with machine tools. The authors have come to the conclusion that literary and technical texts should imply different approaches for adaptation and simplification. In addition, personal readers’ experience plays a great part in finding the implications in literary texts. In this respect it might be reasonable to create separate engines for simplifying and adapting texts from diverse spheres of knowledge.
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Antonova, A. (2011) Empathy as Speech Manipulation Target in Pre-election Discourse of Great Britain. GEMA Online® Journal of Language Studies. 11(3), 97-107. http://journalarticle.ukm.my/2764/
Bakhtin, M.M. (2000) The problem of speech genres. Author and hero. To the philosophical foundations of the humanities. St. Petersburg: Azbuka.
Bhargava, R., & Sharma, Y. (2020). Deep Extractive Text Summarization. Procedia Computer Science, 167, 138–146. URL: https://www.sciencedirect.com/science/article/pii/S1877050920306566
Bogin, G.I. (2001). Obtaining Ability to Understand: Introduction to Hermeneutics. Tver’: Tver’ State University.
Brygina, A.V. (2005) About Some Methods of Text Adaptation on Content and Meaningful Levels. RUDN Journal of Language Studies. Linguistics. 7, 84-88. https://cyberleninka.ru/article/n/o-nekotoryh-printsipah-adaptirovaniya-teksta-na-soderzhatelno-smyslovom-urovne
Cao, M., & Zhuge, H. (2020). Grouping Sentences As Better Language Unit for Extractive Text Summarization. Future Generation Computer Systems. 109, 331–359. https://www.sciencedirect.com/science/article/abs/pii/S0167739X19318989
Chernyavskaya V. E. (2009) Linguistics of the text. Polycode content. Intertextuality. Interdiscursivity. Moscow.
Chouchani, N., & Abed, M. (2020). Automatic Generation of Personalized Applications Based on Social Media. Procedia Computer Science. 170, 825–830. https://www.sciencedirect.com/science/article/pii/S1877050920306050
Collados, J.C. (2013). Splitting Complex Sentences for Natural Language Processing Applications: Building a Simplified Spanish Corpus. 5th International Conference on Corpus Linguistics. Procedia – Social and Behavioral Sciences. 95(2013), 464–472.
https://www.sciencedirect.com/science/article/pii/S1877042813041906
Demyankov, V.Z. (1999) Interpretation As a Tool and As an Object of Linguistics. Issues of Philology. 2, 5 – 13. http://www.infolex.ru/Interpret.html
Drozdova, T.V. (2003). The Problem of Understanding a Scientific Text. Astrakhan: AGTU. http://cheloveknauka.com/nauchnyy-tekst-i-problemy-ego-ponimaniya
Dumitrache, I.-C., & Dumitraşcu, V. (2014). The Principle of Personalization – The Basis for an Efficient Educational Process. Procedia – Social and Behavioral Sciences. 128, 463–468. https://www.sciencedirect.com/science/article/pii/S1877042814022800
Duskaeva, L. R. (2004) Dialogic nature of newspaper speech genres: Autoref. diss. ... dr. philol. nauk. St. Petersburg.
Fry, E. A (1968). Readability Formula That Saves Time. Journal of Reading. 11(7), 265–271.
Galperin, I. R. (2008). Text as an object of linguistic research. Moscow.
Karasik, V.I. (2002). Language of Social Status. Moscow: ITDGK “Gnozis”.
Kornilov, O.A. (2003). Linguistic World-Image as Derived National Mentalities. Moscow: CheRo.
Lotman, M. Yu. (1992). Selected articles in 3 volumes. - Vol. 1 Articles on semiotics and typology of cultures. – Tallinn.
Man, Y. (2014). Feature Extension for Short Text Categorization Using Frequent Term Sets. Procedia Computer Science. 31, 663–670. https://www.sciencedirect.com/science/article/pii/S1877050914004918
Maugham, S. (2009). A Man with The Scar and Other Stories. Adapted by G.K. Magidson-Stepanova. Tasks made by L.T. Dobrovol’skaya. Moscow: Airis-press.
Maugham, S. (1992). Collected Short Stories. Penguin Twentieth-Century Classics.
Mishankina, N.A. (2015). The Pragmatics of Scientific Discourse. Vestnik NGPU. 2(24), 126–133. https://cyberleninka.ru/article/n/pragmatika-nauchnogo-diskursa/viewer
Moradi, M. (2018). CIBS: A Biomedical Text Summarizer Using Topic-Based Sentence Clustering. Journal of Biomedical Informatics. 88, (December 2018), 53–61. https://www.sciencedirect.com/science/article/pii/S1532046418302156
Nygard Larsson, P. (2018). “We’re Talking about Mobility”: Discourse Strategies for Promoting Disciplinary Knowledge and Language in Educational Contexts. Linguistics and Education. 48, 61–75. https://www.sciencedirect.com/science/article/pii/S0898589818301268
Ozhegov, S.I., & Shvedova, N.Y. (1999). Explanatory Dictionary of the Russian language. Мoscow: Аzbukovnik
Perelman, Y.I. (2008). To the Methodology of Scientific Popularization. Vestnik MGU. Part 20: Teacher Education. 3, 122–126. https://cyberleninka.ru/article/n/k-metodike-nauchnoy-populyarizatsii
Platonova, Iu., & Tarasova, E., & Golubinskaya, A. (2015). Creolized Text as a Form of Modern Educational Discourse. Worldwide Trends in the Development of Education and Academic Research, 15-18 June 2015. Procedia – Social and Behavioral Sciences. 214, 788–796.
https://www.sciencedirect.com/science/article/pii/S1877042815060747
Pocheptsov, G.G. (1986). About Communicative Typology of the Addressee. Speech Acts in Linguistics and Methodology: Coll.of scient.papers. Pyatigorsk: Pub.house TGPIIY.
Sukhenko, N.V. (2016). The Specifics of the Popularization of Science in Russia. Vestnik NGTU after R.E. Alekseev. Part: Management in Social Systems. Communicative Technologists. 4, 18–22. https://cyberleninka.ru/article/n/spetsifika-populyarizatsii-nauki-v-rossii
Vasileva, T.YU. (2015). Tasks for the Popularization of Science, Innovative and Technological Development, Programs for Promoting Expert Knowledge in the Media. Russia: Trends and Development Prospects: Collection of Articles. Moscow: INION RAN. https://cyberleninka.ru/article/n/zadachi-
populyarizatsii-nauki-innovatsionnogo-i-tehnologicheskogo-razvitiya-programmy-prodvizheniya-ekspertnyh-znaniy-v-sredstva
Vorobyova, O. P. (1993) Linguistic aspects of the addressability of a literary text: monolingual and interlanguage communication. Moscow.
Zhidkov, A.V. (2014). Scientific and Technical Language and Scientific and Technical Translation. Science Time. 5, 67–71. https://cyberleninka.ru/article/n/nauchno-tehnicheskiy-yazyk-i-nauchno-tehnicheskiy-perevod
DOI: http://dx.doi.org/10.17576/gema-2021-2103-03
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