O‘ZBEK TILI SENTIMENT ANALIZNING NAZARIY MASALALARI
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sentiment tahlil, tonallik, ma’lumotlar bazasi, avtomatik tahlil, dominant so‘z, teazurus, qoidaga ko‘ra tahlil, mashina ta’limi tahlili##article.abstract##
Ushbu maqolada o‘zbek tili matnlarini sentiment tahlil qilishning umumiy nazariy masalalari tahlilga tortilgan. Avtomatik tahlil uchun lingvistik bilimlar bazasi hamda korpus zarur hisoblanadi. Sentiment analiz fikr bildiruvchilarning munosabatiga ko‘ra neytral, ijobiy va salbiy bo‘lishi mumkin. O‘rganilgan tadqiqotlar tahliliga ko‘ra bildirilayotgan munosabatlarning to‘rt komponenti mavjud: munosabat subyekti, munosabat obyekti, munosabat aspekti, munosabat turi. Shunga ko‘ra o‘zbekcha matnlarni sentiment tahlil qilishda o‘rganilayotgan tadqiqot obyekti sifatida korpus va tezaurusdan foydalaniladi. Shunga ko‘ra maqolada kishilarning munosabat bildirish holati emotsiya, kayfiyat, sotsial munosabat, hissiy munosabat, shaxsiy xulq-atvor kabi atributlarga ko‘ra farqlanishi misollar yordamida dalillangan. O‘zbek tili sentiment analizi dasturini yaratish dunyo tajribasida sinalgan WordNet-Affect, SentiWordNet, SenticNet, MPQA Opinion Corpus, РуСентиЛекс kabi dasturiy ta’minotlar misolida erishilgan ilmiy natijalaridan foydalanish maqsadga muvofiq ekanligi ta’kidlangan.
Библиографические ссылки
Jurafskiy D., James H. Martin Speech and language processing. An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition, 2007 –P. 397.
Зверева П.П. Сентимент-анализ текста (на материале печатных текстов газеты «The New York Times» о России и россиянах) / Вестник МГОУ. Серия: Лингвистика, 2014 / № 5. – C. 33.
Scherer, K. R. (2000). Psychological models of emotion. In Borod, J. C. (Ed.), The neuropsychology of emotion, Oxford.pp. –137–162.
Ергеш Бану Определение тональности текстов на казахском языке на основе словаря эмоциональной / Turklang.2017 international conference –Kazan, 2017. – С. 63-64.
X. Li. D. Roth, Learning Question Classifiers: The Role of Semantic Information, Natural Language Engineering 1 (1): 000–000. Cambridge University Press. 2004.
Bryan S.Todd An introduction to expert systems. Oxford university (monograph), 1992. –101 p.
Vibhakti V. Bhaire, Ashiki A. Jadhav, Pradnya A. Pashte, Mr. Magdum P.G SPELL CHECKER / International Journal of Scientific and Research Publications, Volume 5, Issue 4, April 2015.
Galitsky, B. Machine Learning of Syntactic Parse Trees for Search and Classification of Text. Engineering Application of AI, http://dx.doi.org/10.1016/j.engappai. 2012.
Galitsky B., Ivovsky D., Kuznetsov S. Parse thicket representations of text paragraphs, «Диалог» (2013) Выпуск 12, – P 241.
Abdurakhmonova N. Tuliyev U. Spell checking analysis of Uzbek texts using Djaro Winkler algorithm / Turklang. 2018 international conference. – Tashkent, 2018 –P. 311-314.
N. Abdurakhmonova, I. Alisher and R. Sayfulleyeva, "MorphUz: Morphological Analyzer for the Uzbek Language," 2022 7th International Conference on Computer Science and Engineering (UBMK), 2022, pp. 61-66, doi: 10.1109/UBMK55850.2022.9919579.
Abdurakhmonova N. The bases of automatic morphological analysis for machine translation. Izvestiya Kyrgyzskogo gosudarstvennogo tekhnicheskogo universiteta. 2016;2 (38):12-7.
Abdurakhmonova N, Tuliyev U. Morphological analysis by finite state transducer for Uzbek-English machine translation/Foreign Philology: Language. Literature, Education. 2018(3):68.
Mengliev D, Barakhnin V, Abdurakhmonova N. Development of Intellectual Web System for Morph Analyzing of Uzbek Words. Applied Sciences. 2021; 11(19):9117. https://doi.org/10.3390/app11199117
Abdurakhmonova N., Tuliyev U. and Gatiatullin A., "Linguistic functionality of Uzbek Electron Corpus: uzbekcorpus.uz," 2021 International Conference on Information Science and Communications Technologies (ICISCT), 2021, pp. 1-4, doi: 10.1109/ICISCT52966.2021.9670043.
Kubedinova L. Khusainov A., Suleymanov D., Gilmullin R., Abdurakhmonova N. First Results of the TurkLang-7 Project: Creating Russian-Turkic Parallel Corpora and MT Systems. Proceedings of the Computational Models in Language and Speech Workshop (CMLS 2020) co-located with 16th International Conference on Computational and Cognitive Linguistics (TEL 2020) .2020/11: 90-101.
Abduraxmonova N. Kompyuter lingvistikasi (darslik), Toshkent: Nodirabegim, 2021. – 400 b.
